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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…mehr

Produktbeschreibung
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.
Autorenporträt
Khushboo Pachori è professore associato presso l'OIST di Bhopal. Ha conseguito il dottorato e il master presso la Jaypee University of Engineering & Technology (JUET), Guna (M.P.). Ha conseguito la laurea in ingegneria elettronica presso la Rajiv Gandhi Technical University (RGTU) di Bhopal nel 2010. I miei interessi di ricerca includono IA, ML, elaborazione del segnale e comunicazioni wireless.