A Subband Adaptive Learning Algorithm for Microphone Array Based Speech Enhancement

2005 ◽  
pp. 592-597 ◽  
Author(s):  
Dongxia Wang ◽  
Fuliang Yin
Keyword(s):  
Speech Enhancement ◽  
Adaptive Learning ◽  
Learning Algorithm ◽  
Microphone Array

Adaptive Learning Algorithm for Cerebellar Model Articulation Controller: Neural Network Based Hybrid-Type Controller—Part I

2000 ◽  
Author(s):  
Magdy Mohamed Abdelhameed ◽  
Sabri Cetinkunt
Keyword(s):  
Neural Network ◽  
Control System ◽  
Adaptive Learning ◽  
Learning Algorithm ◽  
Cerebellar Model Articulation Controller ◽  
Neural Network Learning ◽  
Network Learning ◽  
Hybrid Type ◽  
Cmac Neural Network ◽  
Learning Technique

Abstract Cerebellar model articulation controller (CMAC) is a useful neural network learning technique. It was developed two decades ago but yet lacks an adequate learning algorithm, especially when it is used in a hybrid- type controller. This work is intended to introduce a simulation study for examining the performance of a hybrid-type control system based on the conventional learning algorithm of CMAC neural network. This study showed that the control system is unstable. Then a new adaptive learning algorithm of a CMAC based hybrid- type controller is proposed. The main features of the proposed learning algorithm, as well as the effects of the newly introduced parameters of this algorithm have been studied extensively via simulation case studies. The simulation results showed that the proposed learning algorithm is a robust in stabilizing the control system. Also, this proposed learning algorithm preserved all the known advantages of the CMAC neural network. Part II of this work is dedicated to validate the effectiveness of the proposed CMAC learning algorithm experimentally.

An E/H Control Design for a Hydraulic Variable Displacement Axial Piston Motor

2011 ◽  
Author(s):  
Hongliu Du
Keyword(s):  
Adaptive Learning ◽  
Lower Cost ◽  
Learning Algorithm ◽  
Control Design ◽  
Test Results ◽  
Satisfactory Performance ◽  
Control Scheme ◽  
Variable Displacement ◽  
System Uncertainties ◽  
Axial Piston

A simple and novel speed control scheme for variable displacement motors has been developed under the consideration of some system uncertainties. Theoretical analysis and experimental test results have shown that the proposed control strategy is capable of driving the swashplate to track its desired trajectory with robust stability and satisfactory performance. An adaptive learning algorithm enables the controls to automatically adjust for uncertainties in the control bias current. Compared with its hydro-mechanical counterpart, the provided E/H control results in a hydraulic variable displacement motor with lower cost and better performance.

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