Sercan Aygun

Design of a fully-differential double folded cascode class AB opamp with continuous time common mode feedback network for 12-bit pipeline ADC applications

This paper deals with a fully differential (FD) operational amplifier (opamp) consists of double folded cascode and class AB output with continuous time common mode feedback (CMFB) network. The opamp is designed in 0.18 μm CMOS technology in Cadence Spectre Circuit Simulator with 1.8 V supply. In this single supply, opamp has 117 dB gain, 65-degree phase margin, 72 dB common-mode rejection ratio (CMRR) for 2pF load with a power consumption of only 1.2 mW. This topology is more suitable for high-speed pipeline Analog-to-Digital converters (ADCs) with foreground calibration, when compared to conventional designs, enabling operation at higher clock frequencies as the class AB stage causes the slew limiting in the first stage and power dissipation is decreasing.

1 5 Bit Stage 12 Bit Pipeline ADC Design with Foreground Calibration

In this paper, 12-Bit pipeline ADC is to be designed together with caring non-idealities. Pipeline issue in modern computers is quite advantageous for performance. Such structure can be constructed in analog-to-digital converters to make the performance faster. By considering the non-ideal cases for the design, more realistic outputs are expected. There are several non-ideal effects that lower the ADC performance such as gain error and capacitor mismatches. By using calibration techniques like background or foreground calibration, non-ideal effects can be reduced. In this paper, foreground calibration technique is applied and tabloid results are presented at the end. Modelling of the pipeline ADC is constructed on Matlab Simulink environment. Keywords—ADC, data converter, foreground, non-idealities, pipeline, sample and hold

Python based parallel application of Knuth-Morris-Pratt algorithm

Parallel computations in multicore architectures are in big interest these days. Nearly all newly manufactured computers have multicores inside, so these architectures must be efficiently used. In this paper, we introduce the effect of parallel algorithms and multiprocessing in the Knuth-Morris-Pratt, KMP searching algorithm. Searching algorithms in computer science are used in many applications and their complexity analysis is important. More crucially, reducing the computation time heals the success of the application itself especially in the big data. Therefore, the previously proposed KMP algorithm is become parallel which runs on Python development environment in this study. Computation time and speed-up are going to be inspected at the end of the work. This work actually constructs a framework for electronics circuit design and image processing concepts in terms of parallel synthesis and multiprocessing applications for further researches. Parallel KMP is to be used in parallel image processing applications for further researches. This paper is organized by first giving the definition of the string search algorithm together with details of KMP algorithm in the sequential fashion. Then, parallelization of the algorithm is going to be presented by showing the performance details like timing and speed up.