2003•Unpublished venueRequires access

A systematic technique for optimizing one-stage two-filter linear-phase FIR filters for sampling rate conversion

P. Arian, T. Saramäki

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Abstract

It is well-known that the computational complexity of a one-stage linear-phase finite-impulse response (FIR) decimator (interpolator) can be drastically reduced by using an additional linear-phase FIR filter at the output sampling rate (at the input sampling rate). The main difficulty in synthesizing these decimators and interpolators is to find the orders for these filters as well as their frequency-response shaping responsibilities for minimizing the overall number of multipliers per input (output) sample in the decimation (interpolation) case. This paper proposes a systematic approach for solving this problem.

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What this paper is about

It is well-known that the computational complexity of a one-stage linear-phase finite-impulse response (FIR) decimator (interpolator) can be drastically reduced by using an additional linear-phase FIR filter at the output sampling rate (at the input sampling rate). The main difficulty in synthesizing these decimators and interpolators is to find the orders for these filters as well as their frequency-response shaping responsibilities for minimizing the overall number of multipliers per input (output) sample in the decimation (interpolation) case. This paper proposes a systematic approach for solving this problem.

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Available abstract

It is well-known that the computational complexity of a one-stage linear-phase finite-impulse response (FIR) decimator (interpolator) can be drastically reduced by using an additional linear-phase FIR filter at the output sampling rate (at the input sampling rate). The main difficulty in synthesizing these decimators and interpolators is to find the orders for these filters as well as their frequency-response shaping responsibilities for minimizing the overall number of multipliers per input (output) sample in the decimation (interpolation) case. This paper proposes a systematic approach for solving this problem.

Key concepts: Finite impulse response, Decimation, Linear phase, Cascaded integrator–comb filter, Linear filter, Digital filter, Control theory (sociology), Sampling (signal processing)

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