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Design of FIR Filter Based on Cosine-basis Neural Network

Haixia Xu

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Abstract

A method of design of FIR filter based on neural network is proposed in this paper. Amplitude-frequency FIR filter with linear phase is characteristic of finite fourier progression. So a neural mode of cosine basis with three layers is set up, and optional net nodes are discussed. Simulation result shows that better result can be achieved to all kinds of digital filter. There is no fluctuating, frequency value is easy to control precisely.

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What this paper is about

A method of design of FIR filter based on neural network is proposed in this paper. Amplitude-frequency FIR filter with linear phase is characteristic of finite fourier progression. So a neural mode of cosine basis with three layers is set up, and optional net nodes are discussed. Simulation result shows that better result can be achieved to all kinds of digital filter. There is no fluctuating, frequency value is easy to control precisely.

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Available abstract

A method of design of FIR filter based on neural network is proposed in this paper. Amplitude-frequency FIR filter with linear phase is characteristic of finite fourier progression. So a neural mode of cosine basis with three layers is set up, and optional net nodes are discussed. Simulation result shows that better result can be achieved to all kinds of digital filter. There is no fluctuating, frequency value is easy to control precisely.

Key concepts: Filter (signal processing), Finite impulse response, Linear phase, Raised-cosine filter, Filter design, Artificial neural network, Basis (linear algebra), Set (abstract data type)

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