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Quadrature mirror filter

About: Quadrature mirror filter is a research topic. Over the lifetime, 955 publications have been published within this topic receiving 28900 citations.


Papers
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Proceedings ArticleDOI
01 Sep 2015
TL;DR: Simulation results articulate that the proposed CRPSO algorithm outperforms its counterparts PSO not only in terms of quality output, i.e. sharpness at cut-off, pass band ripple and stop band attenuation but also in convergence speed with assured fidelity.
Abstract: In this paper, a superior version of Particle Swarm Optimization called Craziness based Particle Swarm Optimization (CRPSO) Technique is demonstrated for designing two-channel Quadrature Mirror Filter (QMF) Bank so as to process an audio signal with nearly perfect reconstructed output. Apart from achieving a better control on cognitive and social components of standard PSO, the proposed CRPSO dictates better implementation due to incorporation of a fresh craziness parameter, in the velocity equation of PSO, to ensure that the particle would have a predefined craziness probability to maintain the diversity of the particles. This mutation in the velocity equation not only ensures the faster searching in the multidimensional search space but also the solution produced is nearly accurate to the global optimal solution. The algorithm's performance is studied with the comparison of traditional PSO. Simulation results articulate that the proposed CRPSO algorithm outperforms its counterparts(PSO) not only in terms of quality output, i.e. sharpness at cut-off, pass band ripple and stop band attenuation but also in convergence speed with assured fidelity.

2 citations

Book ChapterDOI
01 Jan 2014
TL;DR: In this paper, an alternative approach to the block-transform approach to spatial decorrelation, based on hierarchical subband decompositions, is described, which enables perfect reconstruction in the absence of quantization.
Abstract: The purpose of this chapter is to describe an alternative approach to the block-transform approach to spatial decorrelation, based on hierarchical subband decompositions. This chapter firstly examines the basic two-channel filter bank structure and then investigates the filter properties that enable perfect reconstruction in the absence of quantization. It then goes on to consider the more general case of multirate filtering, showing how, through the appropriate combination of filters and up- and downsampling operations, critical sampling can be achieved. It next examines specific cases of useful subband and wavelet filters and extends the basic architecture to the case of a multistage (multiscale) decomposition and to two dimensions, as required for image compression applications. Finally, bit allocation strategies and scalability are discussed in the context of the JPEG2000 still image coding standard. Examples are provided throughout.

2 citations

Proceedings ArticleDOI
06 Nov 1985
TL;DR: The precise modeling of a digital filter structure through expanded state equations is used as a basis for scaling the filter states and summers to give an improved signal-to-noise ratio for the same filter dynamic range.
Abstract: The precise modeling of a digital filter structure through expanded state equations is used as a basis for scaling the filter states and summers. The scaling process is structured to allow each state and summer full utilization of its dynamic range. The scaling process is user defined and includes, but is not limited to, 1 norms, peak magnitude filter operation, and ran8om noise. The measured dynamic range is then used to "normalize" the summer and state dynamic ranges by changing or adding filter multipliers. This scaling process does not change the basic filter structure. Ihe scaling gives an improved signal-to-noise ratio for the same filter dynamic range. The scaling process has been computer automated for an arbitrary filter.

2 citations

Patent
19 Oct 2010
TL;DR: In this article, a sound signal processing apparatus for converting an input sound signal sequence by use of a predetermined adjustment factor comprises: a filter bank (2601) that is operative to convert an input signal sequence to a Quadrature Mirror Filter (QMF) factor sequence by using a QMF analysis filter; and an adjusting unit (2602) for adjusting the QMF factor sequence.
Abstract: Provided is a sound signal processing apparatus capable of performing a sound signal processing, such as time scaling or frequency modulation, with only a small calculation amount. A sound signal processing apparatus for converting an input sound signal sequence by use of a predetermined adjustment factor comprises: a filter bank (2601) that is operative to convert an input sound signal sequence to a QMF (Quadrature Mirror Filter) factor sequence by use of a QMF analysis filter; and an adjusting unit (2602) for adjusting the QMF factor sequence by causing the QMF factor sequence to be dependent on the predetermined adjustment factor.

2 citations

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231
20227
20214
20203
20197
201812