Yong Lim

Bio: Yong Lim is an academic researcher from National University of Singapore. The author has contributed to research in topics: Band-stop filter & Constant k filter. The author has an hindex of 1, co-authored 1 publications receiving 470 citations.

Frequency-response masking approach for the synthesis of sharp linear phase digital filters

Abstract: If each delay element of a linear phase low-pass digital filter is replaced by M delay elements, an (M + 1) -band filter is produced. The transition-width of this (M + 1) -band filter is 1/M that of the prototype low-pass filter. A complementary filter can be obtained by subtracting the output of the (M + 1) -band filter from a suitably delayed version of the input. The complementary filter is an (M + 1) -band filter whose passbands and stopbands are the stopbands and passbands, respectively, of the original (M + 1) -band filter. If the frequency responses of the original ( M + 1) -band filter and its complementary filter are properly masked and recombined, narrow transition-band filter can be obtained. This technique can be used to design sharp low-pass, high-pass, bandpass, and bandstop filters with arbitrary passband bandwidth.

Design of computationally efficient interpolated FIR filters

Abstract: The number of multipliers required in the implementation of interpolated FIR (Finite-impulse response) filters in the form H(Z)=F(z/sup L/)G(z) is studied. Both single-stage and multistage implementations of G(z) are considered. Optimal decompositions requiring fewest number if multipliers are given for some representative low-pass cases. An efficient algorithm for designing these filters is described. It is based on iteratively designing F(z/sup L/) and G(z) using the Remez multiple-exchange algorithm until the difference between the successive stages is within the given tolerance limits. A novel implementation for G(z) based on the use of recursive running sums is given. The design of this class of filters is converted into another design problem to which the Remez algorithm is directly applicable. The results show that the proposed methods result in significant improvements over conventional multiplier efficient implementations of FIR digital filters. >

The optimum design of one- and two-dimensional FIR filters using the frequency response masking technique

Abstract: An expression for the impulse response up-sampling ratio M, which will produce a minimum complexity design, is derived. It is shown that M approaches e (the base of the natural logarithm) as the number of frequency response masking stages increases; in a K-stage design the complexity of the filter is inversely proportional to the (K+1)th root of the transition width; the frequency response masking technique is effective if the normalized transition width is less than 1/16; and the frequency response masking technique is more efficient than the interpolated impulse response technique if the square root of the normalized transition width is less than the arithmetic mean of the normalized passband edge and stopband edge. An expression for the multistage frequency response ripple compensation is derived. An optimum design relationship for the interpolated impulse response technique is also derived. The design of narrow-band two-dimensional filters using the frequency response masking technique is also presented. >

Linear Programming Algorithms for Sparse Filter Design

Abstract: In designing discrete-time filters, the length of the impulse response is often used as an indication of computational cost. In systems where the complexity is dominated by arithmetic operations, the number of nonzero coefficients in the impulse response may be a more appropriate metric to consider instead, and computational savings are realized by omitting arithmetic operations associated with zero-valued coefficients. This metric is particularly relevant to the design of sensor arrays, where a set of array weights with many zero-valued entries allows for the elimination of physical array elements, resulting in a reduction of data acquisition and communication costs. However, designing a filter with the fewest number of nonzero coefficients subject to a set of frequency-domain constraints is a computationally difficult optimization problem. This paper describes several approximate polynomial-time algorithms that use linear programming to design filters having a small number of nonzero coefficients, i.e., filters that are sparse. Specifically, we present two approaches that have different computational complexities in terms of the number of required linear programs. The first technique iteratively thins the impulse response of a non-sparse filter until frequency-domain constraints are violated. The second minimizes the 1-norm of the impulse response of the filter, using the resulting design to determine the coefficients that are constrained to zero in a subsequent re-optimization stage. The algorithms are evaluated within the contexts of array design and acoustic equalization.

Frequency-response masking approach for digital filter design: complexity reduction via masking filter factorization

Abstract: It has been reported in several recent publications that the frequency response masking technique is eminently suitable for synthesizing filters with very narrow transition-width The major advantages of the frequency response masking approach are that the resulting filter has a very sparse coefficient vector and that the resulting filter length is only slightly longer than that of the theoretical (Remez) minimum The system of filters produced by the frequency response masking technique consists of a sparse coefficient filter with periodic frequency response and one or more pairs of masking filters Each pair of the masking filters consist of two filters whose frequency responses are similar except at frequencies near the band-edges In this paper, we present three methods for reducing the complexity of the masking filters The success of our technique is due to the fact that each pair of the masking filters can be realized as a cascade of a common subfilter and a pair of equalizers >

Coefficient decimation approach for realizing reconfigurable finite impulse response filters

Abstract: A new approach to implement computationally efficient reconfigurable finite impulse response (FIR) filter is presented in this paper If the coefficients of an FIR filter are decimated by M, ie, if every Mth coefficient of the filter is kept unchanged and remaining coefficients are changed to zeros, a multi-band frequency response will be obtained The resulting frequency responses will have centre frequencies at 2pik/M, where k is an integer ranging from 0 to M-1 If these multi-band frequency responses are selectively masked using inherently low complex wide transition-band masking filters, different low-pass, high-pass, bandpass, and bandstop filters can be obtained If every Mth coefficient is grouped together removing the zero coefficients in between, a decimated frequency response in comparison to the original frequency response is obtained In this paper, we also show the design of a reconfigurable filter bank using the above approach