Finite Impulse Response (Fir) Filter Design Using Neural Network
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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 simu...
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.
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