Souhil Kouda

CONTRIBUTION TO THE ANALYSIS AND MODELING OF THE NON-IDEAL EFFECTS OF PIPELINED ADCs USING MATLAB

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.

Multi-Objective Genetic Algorithm optimization of CMOS operational amplifiers

This work studies the problem of CMOS operational amplifiers (op-amps) optimization. A front Pareto based-MOGA (Multi-Objective Genetic Algorithm) methodology is proposed to optimize the operational amplifier. The proposed approach is used to find the optimal dimensional transistor parameters in order to obtain operational amplifier performances for analog and mixed CMOS-based circuit applications. To evaluate the proposed approach, an example in both time and frequency domains for a two-stage CMOS Operational Transconductance Amplifier (OTA) is presented in 0.18μm process. The simulation results confirm the efficiency of MOGA in determining the device sizes in an analog circuit.

Modeling of thermal-conductivity of smart humidity sensor

This paper presents a design of a smart humidity sensor. First we begin by the modeling of a thermal-conductivity based humidity sensor (THS). Using neuronal networks and Matlab environment to accurately express the non-linearity, the cross sensitivity and the hysteresis of the output sensor used. We have done the training to create an analytical model dasiaTHSpsila. In a second step a linearization, by Matlab program, is applied to THS response whose goal is to create a database for an element of correction dasiaCORRECTORpsila. After that we use the bias matrix and the weights matrix obtained by training to establish the THS model and the CORRECTOR model on PSPICE simulator, where the output of the first is identical to the output of the THS and the last correct its nonlinear response, eliminate the hysteresis effect and the cross sensitivity.

Optimization of TiO2 concentration effect for a chemical humidity sensing mechanism

Purpose – The purpose of this paper is to propose a new approach to optimize the TiO2 concentration on a resistive‐type humidity sensing mechanism (RHSM) based on artificial neural network.Design/methodology/approach – First is the modeling of the sensing mechanism. Using neuronal networks and Matlab environment to accurately express the output of the sensing mechanism, this model thus takes into account the parameter, non‐linearity, hysteresis, temperature and frequency; furthermore, the TiO2 concentration effect on the humidity sensing properties in the model is investigated. In a second step, the Matlab environment is used to create a database for an ideal model for the sensing mechanism, where the response of this ideal model is linear for any above parameters value.Findings – An analytical model for the sensing mechanism “SM” and the ideal model “IM” has been created. The bias matrix and the weights matrix were used to establish the SM model and the IM on performance simulation program with integrate...

Optimization of TiO(2) and PMAPTAC Concentrations of a Chemical Humidity Sensing Mechanism.

This work aims to achieve an optimization of the TiO2 and PMAPTAC concentrations in a chemical resistive-type humidity sensing mechanism (RHSM). Our idea is based primarily on the modeling of the sensing mechanism. This model takes into account the parameters of non-linearity, hysteresis, temperature, frequency, substrate type. Furthermore, we investigated the TiO2 and PMAPTAC effects concentrations on the humidity sensing properties in our model. Secondly, we used the Matlab environment to create a database for an ideal model for the sensing mechanism, where the response of this ideal model is linear for any value of the above parameters. We have done the training to create an analytical model for the sensing mechanism (SM) and the ideal model (IM). After that, the SM and IM models are established on PSPICE simulator, where the output of the first is identical to the output of the RHSM used and the output of the last is the ideal response. Finally a “DIF bloc” was realized to make the difference between the SM output and the IM output, where this difference represents the linearity error, we take the minimum error, to identify the optimal TiO2 and PMAPTAC concentrations. However, a compromise between concentrations, humidity and temperature must be performed. The simulation results show that in low humidity and at temperature more than 25 °C, sample 1 is the best (in alumina substrate). However, the sample 9 represents the best sensor (in PET substrate) predominately for the lowest humidity and temperature.

An Efficient RADFET Sensors Model Using Artificial Neural Network (ANN)

In this work, a new approach is proposed to design the neutron angle and fluence radiation sensor. It is based on an Artificial Neural Network (ANN) model which has the advantage of efficient nonlinear mapping in addition to noise tolerance. This model allows us to obtain the angle and the fluence radiation from the drain source current, the drain source voltage, the gate source voltage and the temperature parameters. The obtained results are nearly closed to the experimental results in the literature.

GA-based modeling of a non-ideal second order low-pass ΣΔ modulator

An approach is presented for the high-level simulation and synthesis of discrete-time modulators based on a simulation-based optimization strategy. The high-level synthesis approach determines both the optimum modulator topology and the required building block specifications, such that the system specifications mainly signal to noise ratio (SNR). A genetic-based differential evolution algorithm is used in combination with a fast dedicated behavioral simulator to realistically analyze and optimize the modulator performance. The approach has been implemented in a MATLAB Optimization tool. Simulation results are shown for both the analysis and optimization capabilities, illustrating the effectiveness of the approach. The selected range of optimized modulator topologies as a function of the modulator specifications for a wide range of values indicate the capabilities of and the performance range covered by the tool.

A voltage driver using the rail to rail operation in CMOS 0, 25 μm technology

A rail to rail input common mode range is an important requirement in operational amplifiers for some applications. The most common method for implementing full range operation is by using a complementary differential pair. It is simply a compound structure that consists of NMOS and PMOS differential pairs connected in parallel. The compound structure achieves rail to rail operation; however, it produces variations in the transconductance over the input common mode range. The variations obstruct the design of an optimal operational amplifier, to avoid the problem of transconductance variations, an other structure, consists of two op-amps one n-type and the other p-type controlled by a digital control system, is proposed to achieve the ldquorail to railrdquo operation. The layout of this structure is involved with CMOS 0.25 mum technology.

Modeling of op-amp nonlinearities in pipelined ADC

In this paper, we present a behavioral SIMULINK model for the simulation of operational amplifiers (op-amp). The model includes most of the nonlinearities which affect the performance of these circuits, such parameters (noise, finite gain, finite bandwidth, and slew-rate).With the proposed models it is possible to accurately predict with fast simulations the linearity of sample and hold (Stll) circuit and Multiply digital-to-analog (MDAC) circuit that constructed the pipelined ADC.

A new stabilisation technique for the voltage driver using the rail to rail operation in CMOS 0, 25 µm technology

In complementary input differential pair circuits, the topology CMOS uses both an nMOS differential pair and a pMOS differential pair connected in parallel however, it produces variations in the transconductance over the input common mode range. To avoid the problem of transconductance variations, a new structure, consists of two op-amps one n-type and the other p-type controlled by a digital control system, is proposed. In this paper we purpose a solution of the instability problem of a voltage driver in 40 mV, and to improve the stability we subtract a constant current through the current mirror added to the driver.