Improving Switched Current Sigma Delta Modulators' Performances via the Particle Swarm Optimization Technique

2010 ◽  
Vol 1 (2) ◽  
pp. 18-33 ◽  
Author(s):  
M. Fakhfakh ◽  
S. Masmoudi ◽  
Y. Cooren ◽  
M. Loulou ◽  
P. Siarry
Keyword(s):  
Signal To Noise Ratio ◽  
Optimization Technique ◽  
Memory Cell ◽  
Sampling Frequency ◽  
Embryonic Cell ◽  
Signal To Noise ◽  
Swarm Optimization ◽  
Sigma Delta ◽  
Switched Current ◽  
Particle Swarm Optimization Technique

This paper presents the optimal design of a switched current sigma delta modulator. The Multi-objective Particle Swarm Optimization technique is adopted to optimize performances of the embryonic cell forming the modulator, that is, a class AB grounded gate switched current memory cell. The embryonic cell was optimized regarding to its main performances such as sampling frequency and signal to noise ratio. The optimized memory cell was used to design the switched current modulator which operates at a 100 MHz sampling frequency and the output signal spectrum presents a 45.75 dB signal to noise ratio.

Improving Switched Current Sigma Delta Modulators’ Performances via the Particle Swarm Optimization Technique

2012 ◽  
pp. 154-170
Author(s):  
M. Fakhfakh ◽  
S. Masmoudi ◽  
Y. Cooren ◽  
M. Loulou ◽  
P. Siarry
Keyword(s):  
Signal To Noise Ratio ◽  
Optimization Technique ◽  
Memory Cell ◽  
Sampling Frequency ◽  
Embryonic Cell ◽  
Signal To Noise ◽  
Swarm Optimization ◽  
Sigma Delta ◽  
Switched Current ◽  
Particle Swarm Optimization Technique

This paper presents the optimal design of a switched current sigma delta modulator. The Multi-objective Particle Swarm Optimization technique is adopted to optimize performances of the embryonic cell forming the modulator, that is, a class AB grounded gate switched current memory cell. The embryonic cell was optimized regarding to its main performances such as sampling frequency and signal to noise ratio. The optimized memory cell was used to design the switched current modulator which operates at a 100 MHz sampling frequency and the output signal spectrum presents a 45.75 dB signal to noise ratio.

A High Bandwidth Sigma-Delta Modulator Applied in Micro-Gyroscope

2013 ◽  
Vol 562-565 ◽  
pp. 369-373 ◽  
Author(s):  
Qiang Fu ◽  
Wei Ping Chen ◽  
Song Chen ◽  
Peng Fei Wang ◽  
Xiao Wei Liu
Keyword(s):  
Signal To Noise Ratio ◽  
System Simulation ◽  
Sampling Frequency ◽  
Effective Number ◽  
Signal To Noise ◽  
Sigma Delta Modulator ◽  
Sigma Delta ◽  
High Bandwidth ◽  
Oversampling Ratio ◽  
Input Level

In this paper a fourth-order single-loop sigma-delta modulator applied in micro-gyroscope is designed. The modulator system chose the fully feedforword structure. The signal bandwidth is 200KHz, oversampling ratio is 64 and sampling frequency is 25.6MHz. By system simulation result in Matlab, the signal to noise ratio (SNR) is 92.3dB and effective number of bits (ENOB) is 15.03bits. The whole circuit of modulator is designed and simulated in Cadence Spectre. It is gotten that the SNR is 78.6dB and changes linearly with input level. When input level is bigger than -4dBFs, the modulator becomes overload.

Materialized View Selection Using Swap Operator Based Particle Swarm Optimization

2021 ◽  
Vol 13 (1) ◽  
pp. 58-73
Author(s):  
Amit Kumar ◽  
T. V. Vijay Kumar
Keyword(s):  
Particle Swarm Optimization ◽  
Data Warehouse ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Selection Problem ◽  
Data Repository ◽  
Swarm Optimization ◽  
View Selection ◽  
Particle Swarm Optimization Technique ◽  
Swap Operator

The data warehouse is a key data repository of any business enterprise that stores enormous historical data meant for answering analytical queries. These queries need to be processed efficiently in order to make efficient and timely decisions. One way to achieve this is by materializing views over a data warehouse. An n-dimensional star schema can be mapped into an n-dimensional lattice from which Top-K views can be selected for materialization. Selection of such Top-K views is an NP-Hard problem. Several metaheuristic algorithms have been used to address this view selection problem. In this paper, a swap operator-based particle swarm optimization technique has been adapted to address such a view selection problem.

Sign in / Sign up

Export Citation Format

Share Document