The increasing architecture complexity of data converters makes it necessary to use behavioral models to simulate their electrical performance and to determine their relevant data features. For this purpose, a specific data converter simulation environment has been developed which allows designers to perform time-domain behavioral simulations of pipelined analog to digital converters (ADCs). All the necessary blocks of this specific simulation environment have been implemented using the popular Matlab simulink environment. The purpose of this paper is to present the behavioral models of these blocks taking into account most of the pipelined ADC non-idealities, such as sampling jitter, noise, and operational amplifier parameters (white noise, finite DC gain, finite bandwidth, slew rate, and saturation voltages). Simulations, using a 10-bit pipelined ADC as a design example, show that in addition to the limits analysis and the electrical features extraction, designers can determine the specifications of the basic blocks in order to meet the given data converter requirements.

The present work analyses the non-ideal effects of pipelined analog-to-digital converters (ADCs), also sometimes referred to as pipeline ADCs, including the non-ideal effects in operational amplifiers (op-amps or OAs), switches and sampling circuits. We study these nonlinear effects in pipelined ADCs built using CMOS technology and switched-capacitor (SC) techniques. The proposed improved model of a pipelined ADC includes most of the non-idealities which affect its performance. This model, simulated using MATLAB, can determine the basic blocks specifications that allow the designer to meet given data converter requirements.

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The design of an interface to a specific sensor induces costs and design time mainly related to the analog part. So to reduce these costs, it should have been standardized like digital electronics. The aim of the present work is the elaboration of a method based on multiobjectives genetic algorithms (MOGAs) to allow automated synthesis of analog and mixed systems. This proposed methodology is used to find the optimal dimensional transistor parameters (length and width) in order to obtain operational amplifier performances for analog and mixed CMOS-(complementary metal oxide semiconductor-) based circuit applications. Six performances are considered in this study, direct current (DC) gain, unity-gain bandwidth (GBW), phase margin (PM), power consumption (P), area (A), and slew rate (SR). We used the Matlab optimization toolbox to implement the program. Also, by using variables obtained from genetic algorithms, the operational transconductance amplifier (OTA) is simulated by using Cadence Virtuoso Spectre circuit simulator in standard TSMC (Taiwan Semiconductor Manufacturing Company) RF 0.18 m CMOS technology. A good agreement is observed between the program optimization and electric simulation.

In this paper, genetic algorithm (GA) has been applied to extract the Schottky-barrier height, ideality factor and series resistance ,this new method presents the effect of wide range temperature of Schottky-barrier diode (SBD) model using forward current-voltage (I-V) characteristics, is discussed. The results found was compared with experimental current-voltage data, it has been confirmed that the proposed method can obtain higher parameter precision with better computational efficiency more easily than other methods.

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The design of an interface to a specific sensor induces costs and design time mainly related to the analog part. So to reduce these costs it should have been standardized like digital electronics. The aim of the present work is the elaboration of a method based on multi objectives genetic algorithms (MOGAS) to allow automated synthesis of analog and mixed systems. This proposed methodology is used to find the optimal dimensional transistor parameters (length and width) in order to obtain operational amplifier performances for analog and mixed CMOS (complementary metal oxide semi-conductor)-based circuit applications. Six performances are considered in this study, DC gain, unity-gain bandwidth, phase margin, power consumption, area, and slew rate. We used the Matlab optimization toolbox to implement the program. Also by using variables obtained from genetic algorithms, the operational transconductance amplifier (OTA) is simulated by using Cadence Virtuoso Spectre circuit simulator in standard TSMC RF 0.18μm CMOS technology. A good agreement is observed between the program optimization and electric simulation.