Finite Impulse Response (Fir) Filter Design Using Neural Network

Khushboo Pachori

ISBN 10: 6204202839 / ISBN 13: 9786204202839

Verlag: LAP LAMBERT Academic Publishing Sep 2021, 2021

Beschreibung

Neuware -The design of Finite Impulse Response (FIR) digital filters has received a great deal of interest over the past two decades. There is a various parameters used for designing FIR filter and therefore, there is always a scope for improvement in the efficiency of the designed filter model. Parallel architecture and fast response makes neural network well suited for real time applications. In this book, filter designing is done based on various algorithms in neural network domain such as Back-propagation Neural Network (BPNN), ADALINE Neural Network and Hopfield Neural Network (HNN). Based on simulation, results are found better than the results given by different researchers and provide an attractive alternative to conventional methods.Books on Demand GmbH, Überseering 33, 22297 Hamburg 64 pp. Englisch.

Bestandsnummer des Verkäufers 9786204202839

Bibliografische Details

• Titel: Finite Impulse Response (Fir) Filter Design Using Neural Network
• Verlag: LAP LAMBERT Academic Publishing Sep 2021
• Veröffentlichungsdatum: 2021
• Sprache: Englisch
• ISBN-10: 6204202839
• ISBN-13: 9786204202839
• Bindung: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

The design of Finite Impulse Response (FIR) digital filters has received a great deal of interest over the past two decades. There is a various parameters used for designing FIR filter and therefore, there is always a scope for improvement in the efficiency of the designed filter model. Parallel architecture and fast response makes neural network well suited for real time applications. In this book, filter designing is done based on various algorithms in neural network domain such as Back-propagation Neural Network (BPNN), ADALINE Neural Network and Hopfield Neural Network (HNN). Based on simulation, results are found better than the results given by different researchers and provide an attractive alternative to conventional methods.