Yong Ching Lim

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In this paper, a novel optimization technique is proposed to optimize filter coefficients of linear phase finite-impulse response (FIR) filter to share common subexpressions within and among coefficients. Existing approaches of common subexpression elimination optimize digital filters in two stages: first, an FIR filter is designed in a discrete space such(More)
Frequency translation of audio signals requires the use of very sharp Hilbert transformer if the low frequency components are to be faithfully translated. Unfortunately, the order of a very sharp Hilbert transformer is very high, resulting in very high arithmetic complexity. The frequency-response masking (FRM) technique has been used very successfully for(More)
The most advanced techniques in the design of multiplierless finite impulse response (FIR) filters explore common subexpression sharing when the filter coefficients are optimized. Existing techniques, however, either suffer from a heavy computational overhead, or have no guarantees on the minimal hardware cost in terms of the number of adders. A recent(More)
Hilbert transformers and half-band filters are two very important special classes of finite-impulse response filters often used in signal processing applications. Furthermore, there exists a very close relationship between these two special classes of filters in such a way that a half-band filter can be derived from a Hilbert transformer in a(More)
Frequency-response masking (FRM) technique produces a filter network which comprises several sub-filters with very sparse coefficient values. If the sub-filters are optimized seperately, the overall filter network will be suboptimal. In this paper, an unconstrained weighted least squares algorithm for simultaneously optimizing the sub-filters generated by(More)