Gain deficit effect in the fractional delay filter design by the window method

2009 ◽  
Author(s):  
Maciej Sac ◽  
Marek Blok
Keyword(s):  
Filter Design ◽  
Window Method ◽  
Fractional Delay ◽  
Fractional Delay Filter

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.

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.

AN ACCURATE FIR APPROXIMATION OF IDEAL FRACTIONAL DELAY FILTER WITH COMPLEX COEFFICIENTS IN HILBERT SPACE

2005 ◽  
Vol 14 (03) ◽  
pp. 497-505 ◽  
Author(s):  
N. BABAII RIZVANDI ◽  
A. NABAVI ◽  
SH. HESSABI
Keyword(s):  
Hilbert Space ◽  
Filter Design ◽  
Good Method ◽  
Accurate Method ◽  
Least Square ◽  
Small Delay ◽  
Fractional Delay ◽  
Fractional Delay Filter ◽  
Complex Coefficients ◽  
The Ideal

This paper presents a low-order and accurate method for the design of FIR fractional delay (FD) filters with complex coefficients. This method employs least square technique in Hilbert space to approximate the ideal FD transfer function with a FIR filter and to calculate its coefficients. The main advantages of the resulting filter are: very good response at all frequencies compared to other FD filter design methods and a good method to create very small delay. Design examples are presented to illustrate the effectiveness of this new design approach.

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.

scholarly journals FIR Filter Design Using Distributed Maximal Flatness Method

2013 ◽  
Vol 59 (1) ◽  
pp. 59-66
Author(s):  
Marek Blok
Keyword(s):  
Filter Design ◽  
Weighting Function ◽  
Error Function ◽  
Fir Filters ◽  
Filter Type ◽  
Narrow Frequency Range ◽  
Fractional Delay ◽  
Fractional Delay Filter ◽  
Fir Filter Design ◽  
Zero Frequency

Abstract In the paper a novel method for filter design based on the distributed maximal flatness method is presented. The proposed approach is based on the method used to design the most common FIR fractional delay filter - the maximally flat filter. The MF filter demonstrates excellent performance but only in a relatively narrow frequency range around zero frequency but its magnitude response is no greater than one. This ,,passiveness” is the reason why despite of its narrow band of accurate approximation, the maximally flat filter is widely used in applications in which the adjustable delay is required in feedback loop. In the proposed method the maximal flatness conditions forced in standard approach at zero frequency are spread over the desired band of interest. In the result FIR filters are designed with width of the approximation band adjusted according to needs of the designer. Moreover a weighting function can be applied to the error function allowing for designs differing in error characteristics. Apart from the design of fractional delay filters the method is presented on the example of differentiator, raised cosine and square root raised cosine FIR filters. Additionally, the proposed method can be readily adapted for variable fractional delay filter design regardless of the filter type.

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