Newton iterative identification method for an input nonlinear finite impulse response system with moving average noise using the key variables separation technique

2014 ◽  
Vol 76 (2) ◽  
pp. 1195-1202 ◽  
Author(s):  
Kepo Deng ◽  
Feng Ding
Keyword(s):  
Impulse Response ◽  
Finite Impulse Response ◽  
Moving Average ◽  
Separation Technique ◽  
Iterative Identification ◽  
Response System ◽  
Identification Method ◽  
Key Variables

scholarly journals Least Squares Based and Two-Stage Least Squares Based Iterative Estimation Algorithms for H-FIR-MA Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Zhenwei Shi ◽  
Zhicheng Ji
Keyword(s):  
Least Squares ◽  
Iterative Algorithm ◽  
Impulse Response ◽  
Finite Impulse Response ◽  
Moving Average ◽  
Two Stage ◽  
Iterative Estimation ◽  
Estimation Algorithms ◽  
Two Stage Least Squares

This paper studies the identification of Hammerstein finite impulse response moving average (H-FIR-MA for short) systems. A new two-stage least squares iterative algorithm is developed to identify the parameters of the H-FIR-MA systems. The simulation cases indicate the efficiency of the proposed algorithms.

scholarly journals On Using a Genetic Algorithm in the Designing of Linear Digital Filters

2020 ◽  
Vol 1 (346) ◽  
pp. 113-124
Author(s):  
Jacek Stelmach
Keyword(s):  
Genetic Algorithm ◽  
Impulse Response ◽  
Digital Filters ◽  
Noise Suppression ◽  
Transfer Functions ◽  
Finite Impulse Response ◽  
Optimal Parameter ◽  
Moving Average ◽  
Infinite Impulse Response ◽  
Input Signals

Digital filters, either as filters with moving average (Finite Impulse Response) or autoregressive filters (Infinite Impulse Response), are widely used in noise suppression, signal processing or extracting information from data streams. Although well‑known theory allows for optimal parameter selection, there still exist such real applications where requirements limit the use of digital filters. One of the most important limitations is the response time delay caused by too many used lagged input signals. The method proposed in the article allows us to estimate filter parameters with a genetic algorithm, decreasing its delay but keeping the requirements important for the user (e.g.: attenuation). Transfer functions of such filters were compared with transfer functions of the most known classical filters.

Recursive–iterative identification method for power converters

2021 ◽  
Author(s):  
Peter Drgona ◽  
Rastislav Stefun ◽  
Slavomir Kascak ◽  
Jan Morgos
Keyword(s):  
Power Converters ◽  
Iterative Identification ◽  
Identification Method

scholarly journals An Outlier Robust Finite Impulse Response Filter With Maximum Correntropy

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 17030-17040
Author(s):  
Yanda Guo ◽  
Xuyou Li ◽  
Qingwen Meng
Keyword(s):  
Impulse Response ◽  
Finite Impulse Response ◽  
Finite Impulse Response Filter ◽  
Impulse Response Filter

scholarly journals NANO-studio, the design environment of filter banks implemented in standard CMOS technology

2021 ◽  
Author(s):  
Andrzej Handkiewicz ◽  
Mariusz Naumowicz
Keyword(s):  
Impulse Response ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Cmos Process ◽  
Digital Cmos ◽  
Additional Advantage ◽  
Analysis And Synthesis ◽  
Optimization Parameters ◽  
Synthesis Filter

AbstractThe paper presents a method of optimizing frequency characteristics of filter banks in terms of their implementation in digital CMOS technologies in nanoscale. Usability of such filters is demonstrated by frequency-interleaved (FI) analog-to-digital converters (ADC). An analysis filter present in these converters was designed in switched-current technique. However, due to huge technological pitch of standard digital CMOS process in nanoscale, its characteristics substantially deviate from the required ones. NANO-studio environment presented in the paper allows adjustment, with transistor channel sizes as optimization parameters. The same environment is used at designing a digital synthesis filter, whereas optimization parameters are input and output conductances, gyration transconductances and capacitances of a prototype circuit. Transition between analog s and digital z domains is done by means of bilinear transformation. Assuming a lossless gyrator-capacitor (gC) multiport network as a prototype circuit, both for analysis and synthesis filter banks in FI ADC, is an implementation of the strategy to design filters with low sensitivity to parameter changes. An additional advantage is designing the synthesis filter as stable infinite impulse response (IIR) instead of commonly used finite impulse response (FIR) filters. It provides several dozen-fold saving in the number of applied multipliers.. The analysis and synthesis filters in FI ADC are implemented as filter pairs. An additional example of three-filter bank demonstrates versatility of NANO-studio software.

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