Statistical Analysis and Optimization for VLSI: Timing and Power (Integrated Circuits and Systems)

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One profound change in the chip design business is that engineers can't put the design precisely into the silicon chips. Chip performance, manufacture yield and lifetime become unpredictable at the design stage. Chip performance, manufacture yield and lifetime can't be determined accurately at the design stage. The main culprit is that many chip parameters -- such as oxide thickness due to chemical and mechanical polish CMP and impurity density from doping fluctuations -- can't be determined precisely, and thus are unpredictable.

The so-called manufacture process variations start to play a big role and their influence on the chip's performance, yield and reliability becomes significant. As a result, how to efficiently and accurately assess the impacts of the process variations of interconnects in the various physical design steps are critical for fast design closure, yield improvement, cost reduction of VLSI design and fabrication processes. In this regard, it is imperative to develop new design methodologies to consider the impacts of various process and environmental uncertainties and elevated temperature on chip performance.

Variational impacts and thermal constraints have to be incorporated into every steps of design process to ensure the reliable chips and profitable manufacture yields. The design methodologies and design tools from system level down to the physical levels have to consider variability and thermal impacts on the chip performance, which calls for new statistical and thermal-aware optimization approaches for designing nanometer VLSI systems.

We have proposed statistical on-chip power grid analysis approaches based spectral stochastic method[ J1,J2,J5,C1,C3,C5,C7,C10], stochastic model order reduction methods [C2C4], stochastic capacitance and inductance extraction techniques [J3,C8, C15], statistical leakage and power total and dynamic power analysis techniques [J4,C11,C13,C14,C16,C17], performance bound and mismatch analysis of analog and mixed-signal circuits [C9, C12,C18], statistical timing analysis [J6,C9] and variational impact analysis on the on-chip cache design [C6].

A book summarized our works in a systemic way will be published by Springer in [B1]. Specifically, we seek the following goals for the project. Sheldon Tan, Professor, Dept. Home Dr. Error message Deprecated function : The each function is deprecated. Principle Investigators Dr. Esteban Tlelo-Cuautle. PI: Sheldon Tan. Project Descriptions Background As VLSI technology scales into the nanometer regime, chip design engineering face several challenges in maintaining historical rates of performance improvement and capacity increase with CMOS technologies.

The new method will first build variational transfer functions from linearized analog circuit by determinant decision diagram DDD based symbolic analysis and affine-like interval arithmetic. We will investigate more conservative affine-like interval arithmetic to reduce conservation. Whereas, a saturated gain above 17dB has been achieved with a gain flatness better than 0. The chip area is 5x3. Certain applications demand band specific linearity i. The shape of the signal waveform changes by altering the amplitude and phase of these harmonics.

This change in shape of the signal affects power efficiency PE in different ways. The effects become more dominant for power amplifiers driving a large load. In this paper, some effects of harmonic cancellation on PE are observed and documented. The waveform used is a square wave in low frequency domain. A dual-band matching network capable of providing impedance matching between two arbitrary frequency dependent complex source and load impedances is reported. A number of case studies are included to demonstrate the effectiveness of the proposed technique for distinct source and load impedances at two arbitrary frequencies of interest.

Improving power consumption and performance of error tolerant applications is the target of the design paradigm known as approximate computing. One of the units of a computational architecture where approximations can be introduced is the memory subsystem, leveraging on the resilience of an application to maintain an acceptable output quality even if its input data are subject to imprecision and errors. This paper proposes and implements the management, in the Linux kernel, of multiple approximate memory banks. Applications can then allocate approximate memory for their data structures selecting between different level of approximation, depending on the requirements on output quality.

This allows to design an architecture where approximate physical memory, instead of being composed of a unit intercepting a single point in the energy-quality tradeoff curve, can be split in multiple banks adopting different tradeoffs between approximation level and energy savings. We finally show a case study in the results, where we explore the allocation of different data structures of a signal processing application, depending on sensitivity to errors and desired output quality. To date nearly all sensor-front-end implementations for spaceborne fluxgate magnetometers are discrete.

In order to assure a lightweight and power efficient design it is therefore crucial to integrate the essential components on a single chip. This work describes the design of highly integrated sensor-frontend elements for spaceborne fluxgate magnetometers. The design of a current-source required for the linearization of the fluxgate magnetometer via current feedback is shown. Harsh environmental conditions mandate the use of system monitoring and temperature calibration. The ADC used for monitoring environmental conditions is implemented as a 2nd order discrete time delta-sigma modulator.

This interface circuit was realized in a nm technology using an active area of less than 1mm2. To evaluate the system performance a verification method is proposed based on a MCU that drives a highly linear chopped 1-bit DAC. The common to differential mode conversion is demonstrated.

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The PDN and its resonance frequencies are the key element for understanding the weakness or robustness of the circuit. The main objective of this work is to study the stress propagation in order to increase the robustness of the MCU against FTB stress. Correlations between resonance frequencies and FTB stress are given. We propose a heuristic generalized modeling aiming to investigate relevant aspects concerning the stability of circuits that combine asynchronous digital gates in feedback networks.

After the theoretical inspection of some specific cases, we propose the design of novel low-complexity digital oscillators, that in FPGAs can reach decorrelation times half the ones of the fastest Ring Oscillator obtainable following conventional methods. Effect of SSN on signal and power integrity on bit microcontroller : modeling and correlation. This model achieves an accurate correlation between measurements done on a bit MCU and Eldo simulations.

Then, features are defined in order to build this accurate model. Having this, a deeper research work can be done only by simulation. This paper discusses a novel approach to EMI filter design, based on parametric charts that allow to achieve optimal damping by matching the winding resistance of the damping inductor with the ratio between filter and damping inductances. The proposed approach simplifies the identification of the smallest commercial components complying with attenuation and efficiency requirements.

Experimental results presented in the paper validate the proposed model and design method. In this paper a piecewise-affine PWA power-loss-dependent inductance behavioral model is proposed, for ferrite-core inductors used in switch-mode power supplies SMPSs. The model expresses the inductance at steady-state as a function of easily-measurable quantities. The PWA formulation leads to a faster computation with respect to the arctangent models available in the literature and allows analytically computing the inductor current based on its voltage.

The model is validated through experimental measurements on a buck converter, showing a reliable prediction of the steady-state inductor current, under different SMPS working conditions. This paper investigates the sensitivity of inductive power transfer systems for electric vehicles battery charging.

The goal of the analysis is to assess the impact of harmonics on the transferred power and on the efficiency, in order to define the main specifications for design and calibration of relevant measurement systems. The resulting model predictions are validated by comparison with PSIM simulations. Numerical models of electrical cables are important to describe accurately signal propagation in electrical networks.


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We are interested in the modeling of cables used in low-voltage electrical networks. We observed that numerical cable models exhibit unrealistically sharp resonances and antiresonances.

Static Timing Analysis(STA) of Digital circuits- Part 1: Combinational circuits

We propose an approach to generate cable models with realistic resonances and antiresonances by modifying the attenuation constant. Since RFID design is typically system-on-chip SoC that integrates multiple functions on a single chip, multi-frequency supply ripples can be observed. Since the supply ripple is a significant input noise for the sensors, the noise reduction is needed to achieve accurate sensor operations.

Firstly, it is necessary to analyze the ripple frequencies from each source. Then, the conventional PMU for the calculation of transfer function is modeled to reveal the system behaviour. Since the crucial factor defining the overall PSR is explained, a system level optimization is given, that requires only a simple modification and can be applied to conventional PMU designs. The simulation results show that the system significantly reduces the input ripple after optimization with an improved PSR from 24 dB to dB.

In this paper, we demonstrate a recently proposed security technique for mixed-signal circuits in the context of a real application. The security technique, called MixLock, is based on logic locking of the digital section of the mixed-signal circuit and can be used as a countermeasure for reverse engineering and counterfeiting. We show the effect that locking has on the recorded audio quality based on a metric that counts the resultant glitches per second and by also providing a link where the interested reader can download and listen to output audio samples for locked and unlocked versions of the Sigma-Delta ADC.

An extraction procedure for the body effect factor is also presented. For validation purposes, extracted parameters were compared with those provided by the foundry MOSIS using traditional rectangular transistors. With this modification better simulation results were obtained. However, designers fluent in HDL languages avoid such closed technology targets due to impossibility to include third party designs or the needed over effort to implement large and complex architectures into it, such as soft core based systems.

In this paper a partially automated workflow to take advantage of the PXI environment while empowering advanced HDL engineers to implement complex architectures is presented with reference to a successful use case example. Time-Dependent Variability has attracted increasing interest in the last years. In particular, phenomena such as Bias Temperature Instability, Hot Carrier Injection and Random Telegraph Noise can have a large impact on circuit reliability, and must be therefore characterized and modeled. For technologies in the nanometer range, these phenomena reveal a stochastic behavior and must be characterized in a massive manner, with enormous amounts of data being generated in each measurement.

In this work, a novel tool with a user-friendly interface, which allows the robust and fullyautomated parameter extraction for RTN, BTI and HCI experiments, is presented. In this paper a post-processing framework is presented that can be applied during the design phase of integrated circuits. The aim of this work is to help designers to identify electromagnetic interference issues of their designs, already during the concept or design phase. The developed tool is mainly written in Python and therefore versatilely usable. In general it can be applied to a large range of potential issues, due to e.

However, this paper focuses on the investigation of changes that are introduced in a current regulator by injecting radio frequency interferences into specific circuit blocks. The main scripts are designed environment independent and can therefore be used for a broad range of simulators. When a particle interacts with the fluorine atoms, energy is released in small volume that acts as a nucleation site, producing a bubble and an acoustic signal, which are sensed by means of a set of ultrasound sensors and high-speed cameras. Each event, detected by threshold crossing approach, presents a specific acoustic signature signal amplitude, duration and bandwidth that can be used to separate the involved particles from background noise and thus detects an eventual WIMP interaction.

This work presents the design of a 45 dB 0. The final 0. The front-end circuit, a trans- impedance amplifier and a summing amplifier, has been designed using a standard nm CMOS technology, and the simulation results with the foundry PDK are included in this work. For a single photoelectron fC , the front-end can achieve a signal-noise ratio above 12 and a jitter better than 45 ns.

This work describes the design of a low-power low-jitter, analog front-end for timing-pixel radiations sensors. This front-end is designed to be part of 4D tracking detectors for future high data rate high energy physics experiments. Gallium nitride GaN based LEDs are a promising technology for microdisplays thanks to the brightness they can provide. However, they have not been widely adopted for this type of applications yet, partly due to the size and complexity of the associated driver circuits.

In this paper, we demonstrate that despite the complexity of the driver circuits, a very small pixel pitch can be achieved thanks to CMOS 3D technology. This paper presents the design and characterization of a new delay-line based demultiplexer Demux. The Demux works by setting the delay of each delay-element in the delay-line equal to the period of the input symbol and the delay of the delay-line equal to the period of the sampling clock. Once the delay-line is sampled, each sampled output represents a unique symbol in the input symbol sequence.

As opposed to the traditional tree architecture Demux, the proposed delay-line Demux dissipates power only in the delay-line. In addition to design simplicity, the delay-line Demux also offers power and area advantages over tree Demux when scaled to a higher channel count. Adaptive notch filtering provides an excellent countermeasure and deterrence against CWI. This paper describes a comparative performance analysis of two different types of adaptive notch filtering algorithms for GPS specific application. These are 1 Direct form 2nd Order and 2 Lattice-Based adaptive notch filter. The AWGN and interference signal power is taken in a wide dynamic range to assess the performance of each individual adaptive algorithms.

Signal to Nosie Ratio SNR is an important parameter for the evaluation of the functionality of the receiver under different conditions. A Fully Adaptive Lattice Notch Filter is proposed, which is able to simultaneously adapt both its coefficient to alter center frequency of notch along with the bandwidth of the notch. The filter demonstrated superior tracking ability and convergence speed than other counterpart.

This generator has been implemented in a 0. The output sequences generated by this system have been subjected to the NIST randomness tests proving that they are indistinguishable from a truly random sequence. Finally, other security-related aspects have been studied proving that the proposed generator is cryptographically secure. The Molecular Field-Coupling Nanocomputing is considered as one of the most promising technologies which are intended to outperform the current CMOS scenario. The information is encoded in the charge distribution of molecules and propagated thanks to intermolecular electrostatic interaction.


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Recent works have discussed the possibility of using monostable molecules to achieve extremely low power computation, encoding the information in the polarization of the molecule. Monostable molecule have been analysed as a single element, yet it is not obvious whether they can be used to propagate the information from molecule to molecule, or the information is lost after few molecules. In this work, we analyze from a theoretical point of view the information propagation in wires realized with monostable molecules. We define a Safe-Operating Area which can be used as a reference by chemists and technologists for the definition of a class of molecules which can be used for digital molecular Field-Coupled Nanocomputing.

In recent years, three-dimensional IC 3D IC has gained much attention as a promising approach to increase IC performance due to their several advantages in terms of integration density, power dissipation and achievable clock frequencies. However, the reliability of 3D ICs regarding soft errors induced by radiation is not investigated yet. The flow starts with identifying the characteristics of the generated transient pulses with respect to the radiation profile and 3D layout of the design. Experimental results achieved applying the approach on a 15nm 3D configurable Look-Up-Table LUT designed on two tiers demonstrated the feasibility of the method, showing the vulnerability characterization of four different functional configurations using eight different types of heavy ions.

A resistive random access memory device based on HfO2 with outstanding nonvolatility is fabricated. A dynamic Verilog-A model obeying the electrochemical metallization conductive filament mechanism is demonstrated. The fluctuation of conductive filament growth is added to this model, and the model is verified by DC voltage scanning. The simulation and experimental data are compared using data processing software. Experimental results verify the good electrical characteristics of the RRAM device.

Modeling of the fluctuations of RRAM devices provides guiding significance to the design of peripheral circuits. This paper proposes long-term reliability management for spatial multitasking GPU architectures. Specifically, we focus on electromigration EM -induced long-term failure of the GPU's power delivery network. A distributed power delivery network model at functional unit granularity is developed and used for our EM analysis of GPU architectures. We use a recently proposed physics-based EM reliability model and consider the EM-induced time-to-failure at the GPU system level as a reliability resource.

For GPU scheduling, we mainly focus on spatial multitasking, which allows GPU computing resources to be partitioned among multiple applications. We find that the existing reliability-agnostic thread block scheduler for spatial multitasking is effective in achieving high GPU utilization, but poor reliability. We develop and implement a long-term reliability-aware thread block scheduler in GPGPU-Sim, and compare it against existing reliability-agnostic scheduler.

In this paper, we propose a new dynamic reliability management DRM approachwith deep reinforcement learning DRL for multicore processors considering device reliability eects hard error and transient error of signal soft error. The proposed method is based on a recently proposed physics-based three-phase electromigration model and an exponential soft error model that considers dynamic voltage and frequency scaling DVFS eects. Applying DRL method can achieve better and exible control quality. Compared with the traditional Q-learning based method, DRL method has better scalability, lower memory and lower computational complexities.

Experimental results show that the proposed method signicantly reduces memory footprint and computational time compared to the traditional Q-learning based method. Integral image IIM is an intermediate image representation, employed in several computer vision algorithms. Although only simple arithmetic operations are required to compute an IIM, the total number of additions increases quadratically with the input image size.

For this reason, the design of hardware architectures able to accelerate the IIM computation receives a great deal of attention. Unfortunately, existing solutions are not appropriate for the integration within high-performance embedded systems, which are currently realized within modern heterogeneous CPU-FPGA System on Chips SoCs. In this paper, we present a novel hardware architecture for accelerating the IIM computation.

The proposed design outperforms existing competitors by parallelizing operations along both rows and columns of the input image. A demo video can be found at [ref] password: rtneu. Tactile data processing still an open challenge, in this paper we will demonstrate a method to achieve touch modality classification using pre-trained Convolutional Neural Network. The 3D tensorial tactile data generated by real human interaction on an electronic skin E-Skin were transformed into 2D images.

Using CNN and Transfer Learning, the feasibility and efficiency of the proposed method, has been proven using a real tactile dataset, and by outperforming classification of the same problem in the literature. Approximate Computing Techniques offer a promising solution to reduce the hardware complexity and power consumption imposed when embedding machine learning algorithms. The reduction comes at the cost of some performance degradation. This paper presents an approximate machine learning classifier for touch modality recognition. Smart imagers modeling and optimization framework for embedded AI applications.

This work presents a framework for behavioral simulations of smart imagers with hardware and power constraints. The objective is to compare innovative imaging systems that would be composed of a specific image sensor and a dedicated image processing. For that purpose, a versatile imager model is presented and applied to a time-to-first-spike imager associated with two types of neural networks. Wearable physiology is an expanding field, especially for sports applications that steadily require an accurate monitoring of the physical status of athletes.

This work presents the co-design and the realization of an hardware front-end that enables multi-sensing of up to four endogenous electrolytes. A pH and temperature readout circuit are included for sensor calibration. The platform is validated with potassium and sodium ions monitoring. The hardware is remotely controlled by an user interface that configures the sensor panel and collects the biological data through a Bluetooth link. The sizes of the frontend circuit allows its integration into a headband, suitable for wearable monitoring in sweat.

Implantable electronic devices are emerging as important healthcare technologies due to their sustainable operation and low risk of infection. To overcome the drawbacks of the built-in battery in implantable devices, energy harvesting from the human body or another external source is required.. Energy harvesting using appropriately sized and properly designed photovoltaic cells enable implantable medical devices to be autonomous and self-powered. Among the challenges in using PV cells is the small fraction of incident light that penetrates the skin. Thus, it is necessary to involve such physical properties in the energy harvesting system design.

Consequently, we propose a novel photodiode model that considers skin loss in different ethnic groups. Circuit and system modelling has been performed using Cadence nm technology. Our results show that the transmittance of near infrared light is almost the same in three skin types: Caucasian, Asian and African. With the help of a power management unit, an output voltage of 1. In this work we present engineering optimization of our battery-operated sensory headwear, which uses an inertial measurement unit to detect the head movements and wireless transmits the acquired data. The manoeuvrability with the head, without the use of hands, makes it ideal for the autonomous use by people with reduced motor skills, such as quadriplegics, for home automation and direct control of actuators.


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The harvester, based on commercial chipset, has been conceived to operate with a custom loop antenna integrated on the headwear. This paper presents an energy-efficient analog front-end circuit to monitor the pulmonary artery pressure PAP with piezoresistive sensors. A low-power capacitively-coupled instrumentation amplifier CCIA is developed in order to boost the amplitude of the bridge sensor to the input range of the analog-to-digital converter ADC.

Simulation results show that this CCIA with chopping technique achieves an input-referred noise density of This gives a noise-efficiency factor NEF of 3. Dual supply voltages are used to decrease the power consumption of the bridge sensor. This low-noise, low-offset analog front-end circuit achieves an accuracy of 0.

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Monitoring of patient response to the anaesthetic drugs is an attractive improvement for achieving a correct balance of sedation level, increasing the chance of success in the right procedure of anaesthesia. Nowadays, there are no commercial tools able to offer real-time monitoring of anaesthetics, indeed, there is still a lack in sensing technologies able to maintain high performances in long term monitoring within a portable miniaturised hardware system.

To overcome these limitations, we are here presenting the innovative concept of a portable pen-device able to sense anaesthetic compounds over time.

Statistical Analysis and Optimization for VLSI: Timing and Power | SpringerLink

This study is based on an electrochemical sensor to be fully integrated into a complete pen-shaped point-of-care for the monitoring of anaesthesia delivery. The design of the system is based on a bio-inspired event-based approach that is guaranteeing low complexity, low power consumption and is therefore suitable to be scaled to fit the barrel of a pen.

In order to achieve a high quality and cost effectiveness in the development process for automotive and consumer applications, an advanced design flow for the MEMS micro electro mechanical systems element is urgently required. In this paper, such a development methodology and flow for parasitic extraction of active semiconductor devices is presented. The methodology considers geometrical extraction and links the electrically active pn-junctions to SPICE standard library models and finally extracts the netlist.

An example for a typical pressure sensor is presented and discussed. Finally, the results of the parasitic extraction are compared with fabricated devices in terms of accuracy and capability. An approach for a mostly automated design and layout of capacitive accelerometers is presented, which permits the efficient synthesis of accelerometers up to 3 axes. Fernandez 1. Reliability in CMOS-based integrated circuits has always been a critical concern. In today's ultra-scaled technologies, a time-varying kind of variability has raised that, on top of the well-known time-zero variability, threatens to shorten the lifetime of integrated circuits, both analog and digital.

Effects like Bias Temperature Instability and Hot Carriers Injection need to be studied, characterized and modeled to include, and, thus, mitigate, their impact in the design of CMOS integrated circuits. This paper presents an array-based integrated circuit whose purpose is precisely that: to observe, quantify and characterize the impact of time-dependent variability effects in a specific kind of circuits: Ring Oscillators. To enable this evaluation, a stochastic reliability simulation flow which combines Monte Carlo simulations with degradation is presented. It makes use of a charged-based degradation aware transistor model incorporating both process variation and aging effects into a normal Spice simulation without the need of an additional aging simulator.

The simulation flow enables the continuous evaluation of the changing stress conditions while keeping the simulation effort at a reasonable level. The analysis is performed on two different flip-flop architectures, a master slave flip-flop and a pulsed flip-flop, to determine the shift of timing performance distributions over time as well as the dependence on temperature. The sensitivity of integrated circuit parameters regarding manufacturing process variation represents a very important ongoing topic in the semiconductor industry.

Establishing the functional relationship between them at an early stage, i. This paper presents a methodology for finding the influence of technology parameters i. Process Control Monitor parameters on device performance.

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The methodology is based on Machine Learning algorithms and Bayesian Optimization framework with the purpose of modelling the functional dependencies between technology and circuit parameters. The experimental results prove that the device performance is highly sensitive to technology parameters variation and this dependency can be modelled. This paper presents an integrated circuit IC array whose purpose is to observe, quantify and characterize the impact of time-dependent variability effects, like aging, in several widely used digital and analog circuit blocks.

With the increasing interest that this kind of mechanism has attracted in the last years, for its potential impact in the reliability of ultra-scaled integrated circuits, it is only relevant that appropriate measures are taken to find out how it can be included and thus mitigated in the design process of such integrated circuits.

And, while substantial literature exists that covers the device level, time-dependent variability at circuit level has not been as equally studied. This work complements our previous efforts in providing a holistic approach to Reliability-Aware Design: from statistical characterization and modeling at device-level, to simulation, and into optimization-based design with reliability considerations, the array presented here provides one more step towards a thorough and accurate understanding of how time-dependent variability works at the circuit level.

Conventionally, evolutionary algorithms are employed during circuit sizing and layout generation processes; thus, time to design can be considerably reduced. Furthermore, yield-aware analog circuit design automation tools have been developed by integrating variability analysis with the optimization. Previous works have mostly focused on improving the efficiency of optimization tools without sacrificing the accuracy. However, the accuracy of design automation tools is still argumentative since they are validated either at the pre- or post- layout level.

But, in practice, post-silicon measurement is mandatory in order to verify the robustness of synthesis tools. To our best knowledge, there is no implementation and verification of yield-aware circuit sizing tools in the literature. In this study, a yield-aware circuit sizing tool is validated on silicon. For that purpose, two different OTA circuits were optimized using a yield-aware circuit sizing tool, a test chip was designed, tapedout, characterized, and results were compared with the results generated by the optimizer.

To evaluate these statistical parameters, the model is based on a combination of measurements to acquire data related to trap population, Technology CAD TCAD simulations and a Matlab routine. Equivalent circuit extraction procedure from Nyquist plots for graphene-silicon solar cells. In this paper an automatic procedure to extract the equivalent circuit from impedance spectroscopy data is reported.

The presented procedure is most suited for multilayer structures and has the advantage to cross the information deriving from impedance spectroscopy data, represented in the form of Nyquist plot, with C-V experimental data, adding physical constraints to the extracting procedure.

Numerical and experimental tests have been performed on graphene-silicon solar cells, exhibiting good results. This paper introduces a novel method of analysis for System-on-Chip SoC development building upon commonly used tools and techniques to approximate and automate the human process of investigation. Knowledge of the interactions between components within a SoC is essential for understanding how a system works so the presented method provides a way of visualizing these interactions. The mathematical basis for the method is explained and justified, then the method is demonstrated using two representative case studies.

Visualizations from the case studies are used to exhibit the usefulness of the method for system optimization, monitoring, and validation. Gallium nitride shows huge potential in power electronics applications. Nevertheless its implementation is still hindered by reliability issues and technology-related dynamic effects. A direct comprehension of their behavior in the final application is still missing.

Hence, the goal of this work is to propose a novel methodology to analyse the role of these phenomena on the end application efficiency. These insights can thus lead to a system-level driven optimization of GaN technology. We propose a method based on T-CAD mixed-mode simulation and we give an example of its implementation in the analysis of a class-E power amplifier for wireless power transfer. Efficiency curve is extracted for different load resistance values. This is carried out for the device both in relaxed and in stressed conditions to evaluate the impact of buffer traps.

It is demonstrated how the main degradation resides in the increased dynamic resistance while threshold voltage shift and output capacitance variations both play a minor role. In this paper, we describe a systematic low-power design methodology for technologies that offer a strong body factor. Specifically, we explore both the body bias voltage and the supply voltage knobs in order to find the MEP minimum energy point for a constant target frequency.

Our methodology accounts for process and temperature PT variations while charting the design space for a simple reference design. We then show how to scale the energy data of this reference design to any arbitrary design. In this work, a paper-based disposable piezoresistive force sensor has been designed, fabricated and tested along with peripheral electronic circuit.

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Strathmore Bristol paper is employed as the substrate and it is coated with graphite and silver ink to form a perforated cantilever beam which constitutes the sensor part of the force sensing system. The implemented sensor has a sensitivity of 8. In addition to the advantages offered by ultrasonic fingerprint sensors based on MEMS technology, the all solid approach used here requires much lower driving voltage and provides higher operative frequency for improved axial resolution, overcoming some of the current limitations present in micromachined ultrasonic transducers. In this work we deal with the restrictions in the PiezoMUMPs process that arise due to the use of standard design rules that place constraints on the thicknesses, and materials that may be used, however, these inconveniences may be partially overcome by taking proper design considerations.

Here we obtain output voltage in the mV range for an applied short pulse of 2 Vp at 1. The advances in MEMS technology offer now the possibility to manufacture loudspeakers, which need special drivers to achieve optimum performance. Digital Design and Computer Architecture 2nd Edition. Fundamentals of Semiconductor Devices. Thallium-Based High-Tempature Superconductors. Silicon Photonics - Part 2 Volume Piezoelectric Sensors and Actuators Fundamentals and Applications. Nanoelectronic Materials Fundamentals and Applications. Silicon Photonics for Telecommunications and Biomedicine. Popular Searches environmental management processes and practices f ka stroud engineering mathematics pdf higher engineering mathematics grewal k a stroud engineering mathematics 7th edition modern engineering mathematics 4th edition.

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