Variable Ratio Sample Rate Conversion Based on Fractional Delay Filter

2015 ◽  
Vol 39 (2) ◽  
pp. 231-242 ◽  
Author(s):  
Marek Blok ◽  
Piotr Drózda
Keyword(s):  
Speech Signal Processing ◽  
Farrow Structure ◽  
Conversion Algorithm ◽  
Window Method ◽  
Voiced Speech ◽  
Fractional Delay ◽  
Sample Rate ◽  
Fractional Delay Filter ◽  
Speech Segments ◽  
Rate Conversion

Abstract In this paper a sample rate conversion algorithm which allows for continuously changing resampling ratio has been presented. The proposed implementation is based on a variable fractional delay filter which is implemented by means of a Farrow structure. Coefficients of this structure are computed on the basis of fractional delay filters which are designed using the offset window method. The proposed approach allows us to freely change the instantaneous resampling ratio during processing. Using such an algorithm we can simulate recording of audio on magnetic tape with nonuniform velocity as well as remove such distortions. We have demonstrated capabilities of the proposed approach based on the example of speech signal processing with a resampling ratio which was computed on the basis of estimated fundamental frequency of voiced speech segments.

Sampling Rate Converison by a Fractional Factor

2009 ◽  
pp. 171-205
Author(s):  
Ljiljana Milic
Keyword(s):  
Conversion Factor ◽  
Filter Design ◽  
Sampling Rate ◽  
Farrow Structure ◽  
Sampling Rate Conversion ◽  
Fractional Delay ◽  
Fractional Sampling ◽  
Rational Factor ◽  
Fractional Delay Filter ◽  
Rate Conversion

We have discussed so far the decimation and interpolation where the sampling rate conversion factor is an integer. However, the need for a non-integer sampling rate conversion appears when the two systems operating at different sampling rates have to be connected, or when there is a need to convert the sampling rate of the recorded data into another sampling rate for further processing or reproduction. Such applications are very common in telecommunications, digital audio, multimedia and others. In this chapter, we consider the sampling rate conversion by a rational factor, called sometimes a fractional sampling rate conversion. We use MATLAB functions from the Signal Processing and Filter Design Toolbox to demonstrate the fractional sampling rate conversion. We present the technique for constructing efficient fractional sampling rate converters based on FIR filters and the polyphase decomposition. In the sequel, we consider the sampling rate alteration with an arbitrary conversion factor. We present the polynomial-based approximation of the impulse response of a hybrid analog/digital model, and the implementation based on the Farrow structure. We also consider the fractional-delay filter problem. This chapter concludes with MATLAB exercises for individual study.

Asynchronous Sampling Rate Conversion of Digital Audio Signal

2014 ◽  
Vol 687-691 ◽  
pp. 4093-4096
Author(s):  
Yan Xue ◽  
Fei Yang
Keyword(s):  
Sampling Rate ◽  
Audio Signal ◽  
Clock Pulse ◽  
Digital Audio ◽  
Rate System ◽  
Asynchronous Sampling ◽  
Sampling Rate Conversion ◽  
Fractional Delay ◽  
Fractional Delay Filter ◽  
Rate Conversion

At present, in the digital audio processing sampling rate is respectively 32 kHz, 44.1 kHz, 48 kHz [1]. Because of the different criteria, there is much inconvenience in the process of research. Therefore, the sampling rate converter is a must, between any two kinds of sampling rate. In synchronous sampling rate conversion, you can use decimation and interpolation for sampling rate conversion, but in the asynchronous sampling rate system, due to the different input clock pulse with the output clock pulse, the above method cannot achieve. Therefore we introduce the fractional delay filter sampling rate conversion. This article introduces the principle of the sampling rate conversion and the fractional delay filter based on Farrow structure. At last, we simulate asynchronous sampling rate conversion of audio signal through the MATLAB.

A Nearly Optimal Fractional Delay Filter Design Using an Asymmetric Window

2011 ◽  
Vol 57 (4) ◽  
pp. 465-472 ◽  
Author(s):  
Maciej Sac ◽  
Marek Blok
Keyword(s):  
Real Time ◽  
Filter Design ◽  
Design Method ◽  
Optimal Filter ◽  
Optimal Filters ◽  
Window Method ◽  
Fractional Delay ◽  
Fractional Delay Filter ◽  
Filter Design Method ◽  
Varying Delay

A Nearly Optimal Fractional Delay Filter Design Using an Asymmetric WindowIn this paper a numerically efficient filter design method suitable for variable fractional delay (VFD) filter implementation is investigated. We propose to use a well known window method with an asymmetric window extracted from optimal filter designed beforehand. As we will demonstrate, such an approach, if additional gain correction is applied, allows for nearly optimal VFD filter design. Thus, the proposed approach combines window method simplicity with performance comparable to that of optimal filters. Efficiency of the presented technique makes it suitable for designing filters with varying delay in real time.

scholarly journals Maximally Flat and Least-Square Co-Design of Variable Fractional Delay Filters for Wideband Software-Defined Radio

2018 ◽  
Vol 28 (01) ◽  
pp. 1950006
Author(s):  
Haolin Li ◽  
Joris Van Kerrebrouck ◽  
Johan Bauwelinck ◽  
Piet Demeester ◽  
Guy Torfs
Keyword(s):  
Software Defined Radio ◽  
Main Idea ◽  
Least Square ◽  
Design Parameters ◽  
Timing Synchronization ◽  
Implementation Cost ◽  
Digital Beamforming ◽  
Farrow Structure ◽  
Fractional Delay ◽  
Rate Conversion

This paper describes improvements in a Farrow-structured variable fractional delay (FD) Lagrange filter for all-pass FD interpolation. The main idea is to integrate the truncated sinc into the Farrow structure of a Lagrange filter, in order that a superior FD approximation in the least-square sense can be achieved. Its primary advantages are the lower level of mean-square-error (MSE) over the whole FD range and the reduced implementation cost. Extra design parameters are introduced for making the trade-off between MSE and maximal flatness under different design requirements. Design examples are included, illustrating an MSE reduction of [Formula: see text] compared to a classical Farrow-structured Lagrange interpolator while the implementation cost is reduced. This improved variable FD interpolation system is suitable for many applications, such as sample rate conversion, digital beamforming and timing synchronization in wideband software-defined radio (SDR) communications.

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