Quantum Inspired Computational Intelligence 2017
DOI: 10.1016/b978-0-12-804409-4.00010-3
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Digital filter design using quantum-inspired multiobjective cat swarm optimization algorithm

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Cited by 6 publications
(8 citation statements)
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“…Literature [18][19][20] provides a new idea of combined time series model for series prediction. Literature [21][22][23][24][25][26][27][28][29][30] mainly discusses the design problems of classical digital filter and adaptive filter. The two kinds of filters have advantages and disadvantages, but the adaptive filter has more restrictions than the classical filter.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Literature [18][19][20] provides a new idea of combined time series model for series prediction. Literature [21][22][23][24][25][26][27][28][29][30] mainly discusses the design problems of classical digital filter and adaptive filter. The two kinds of filters have advantages and disadvantages, but the adaptive filter has more restrictions than the classical filter.…”
Section: Discussionmentioning
confidence: 99%
“…Aiming at the problem that eddy current signals contain relatively serious noise ratio, a group of digital bandpass filters is designed in literature 24 to improve the measurement accuracy. Literature 25 proposes a filter design method based on evolutionary optimization, which provides filter designers with higher degrees of freedom, so that the filter can be shaped in the frequency response of the digital filter to achieve the required specifications. Literature 26 discusses the multiple uses of various digital filters, namely the effects of median, Gaussian, and average on speckle contrast, as well as on phase patterns.…”
Section: Research Status Analysis Of Filter Preprocessing Algorithm F...mentioning
confidence: 99%
“…It is not appropriate to treat the delay of a uniformly sampled band-limited digital signal as a continuous-time signal. To address this issue, the continuous-time signal must be converted into a discrete-time signal through sampling at time instant s t nT  and delaying by a positive real number D, consisting of an integer and fractional part d [1][2] [3]. The resulting delayed discrete signal can be expressed as Eq.…”
Section: The Implementation Principle Of Digital Fractional Delaymentioning
confidence: 99%
“…Dwivedia et al extended the quantum-inspired cat swarm optimization as a Multiobjective algorithm, which uses the idea of Qubits [16]. Murtza et al extended the integer cat swarm optimization as a multi-objective algorithm, which can be used for binary multiobjective problems [17].…”
Section: Introductionmentioning
confidence: 99%