Design of FIR Digital Filters Using Hopfield Neural Network(Digital Signal Processing)

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概要

• 論文の詳細を見る

• This paper is intended to provide an alternative approach for the design of FIR filters by using a Hopfield Neural Network (HNN). The proposed approach establishes the error function between the amplitude response of the desired FIR filter and the designed one as a Lyapunov energy function to find the HNN parameters. Using the framework of HNN, the optimal filter coefficients can be obtained from the output state of the network. With the advantages of local connectivity, regularity and modularity, the architecture of the proposed approach can be applied to the design of differentiators and Hilbert transformer with significantly reduction of computational complexity and hardware cost. As the simulation results illustrate, the proposed neural-based method is capable of achieving an excellent performance for filter design.

• 社団法人電子情報通信学会の論文
• 2007-02-01

著者

• CHEN Fu-Kun

  Department of Computer Science and Information Engineering, Southern Taiwan University

• Chen Fu‐kun

  Southern Taiwan Univ. Twn

• Chen Fu-kun

  The Author Is With The Department Of Computer Science And Information Engineering Southern Taiwan Un

• Chen Fu-kun

  Department Of Computer Science And Information Engineering Southern Taiwan University

• JOU Yue-Dar

  Department of Computer and Information Science

• Jou Yue-dar

  Department Of Computer And Information Science:(present Office)department Of Electrical Engineering

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