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Bacterial Foraging Optimization for Digital Filter Synthesis: A Computational Intelligence Approach to DSP and Image Processing - Softcover
Inhaltsangabe
In any deterministic solution, the convergence is not at all guaranteed, whereas, the stochastic and random search algorithms are 1 shot optimization and it can hit the nearly optimized solution, with guarantee. Therefore the AI dependent evolutionary algorithms (GA, PSO, DE, BFOA) are prescribed for this type of optimization problems. Some selected evolutionary algorithms are presented for digital filter design. If the statistical characteristic of the input data varies with respect to time or the required knowledge about input data is not satisfactory, adaptive filters are needed. Adaptive filters (FIR and IIR) have attractive increasing attention due to their widespread use in many different applications such as system identification, noise cancellation, channel equalization, linear prediction, control, and modeling. In the present book, in order to achieve a global minimum solution to the fitness function related to filter transfer function, biologically inspired algorithm is used. Adaptation to classical Bacterial Foraging Optimization is employed to design stable and optimum digital filter design for signal processing and image processing applications.
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In any deterministic solution, the convergence is not at all guaranteed, whereas, the stochastic and random search algorithms are 1 shot optimization and it can hit the nearly optimized solution, with guarantee. Therefore the AI dependent evolutionary algorithms (GA, PSO, DE, BFOA) are prescribed for this type of optimization problems. Some selected evolutionary algorithms are presented for digital filter design. If the statistical characteristic of the input data varies with respect to time or the required knowledge about input data is not satisfactory, adaptive filters are needed. Adaptive filters (FIR and IIR) have attractive increasing attention due to their widespread use in many different applications such as system identification, noise cancellation, channel equalization, linear prediction, control, and modeling. In the present book, in order to achieve a global minimum solution to the fitness function related to filter transfer function, biologically inspired algorithm is used. Adaptation to classical Bacterial Foraging Optimization is employed to design stable and optimum digital filter design for signal processing and image processing applications.
Biografía del autor
Apurba is working in Imaging Lab of HCL Technologies Ltd., India as Technical Specialist. He has more than 10 years of experience in industry and academic R&D in the domain of Signal Processing, Image Processing and Pattern Recognition. He has plenty of peer-reviewed papers & 5 published books.
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Bacterial Foraging Optimization for Digital Filter Synthesis
Verlag:
LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659434167
ISBN 13: 9783659434167
Neu
Softcover
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Das ApurbaApurba is working in Imaging Lab of HCL Technologies Ltd., India as Technical Specialist. He has more than 10 years of experience in industry and academic R&D in the domain of Signal Processing, Image Processing and Pattern. Bestandsnummer des Verkäufers 5155982
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Bacterial Foraging Optimization for Digital Filter Synthesis
Verlag:
LAP LAMBERT Academic Publishing Aug 2013, 2013
ISBN 10: 3659434167
ISBN 13: 9783659434167
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In any deterministic solution, the convergence is not at all guaranteed, whereas, the stochastic and random search algorithms are 1 shot optimization and it can hit the nearly optimized solution, with guarantee. Therefore the AI dependent evolutionary algorithms (GA, PSO, DE, BFOA) are prescribed for this type of optimization problems. Some selected evolutionary algorithms are presented for digital filter design. If the statistical characteristic of the input data varies with respect to time or the required knowledge about input data is not satisfactory, adaptive filters are needed. Adaptive filters (FIR and IIR) have attractive increasing attention due to their widespread use in many different applications such as system identification, noise cancellation, channel equalization, linear prediction, control, and modeling. In the present book, in order to achieve a global minimum solution to the fitness function related to filter transfer function, biologically inspired algorithm is used. Adaptation to classical Bacterial Foraging Optimization is employed to design stable and optimum digital filter design for signal processing and image processing applications. 216 pp. Englisch. Bestandsnummer des Verkäufers 9783659434167
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Bacterial Foraging Optimization for Digital Filter Synthesis : A Computational Intelligence Approach to DSP and Image Processing
Verlag:
LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659434167
ISBN 13: 9783659434167
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In any deterministic solution, the convergence is not at all guaranteed, whereas, the stochastic and random search algorithms are 1 shot optimization and it can hit the nearly optimized solution, with guarantee. Therefore the AI dependent evolutionary algorithms (GA, PSO, DE, BFOA) are prescribed for this type of optimization problems. Some selected evolutionary algorithms are presented for digital filter design. If the statistical characteristic of the input data varies with respect to time or the required knowledge about input data is not satisfactory, adaptive filters are needed. Adaptive filters (FIR and IIR) have attractive increasing attention due to their widespread use in many different applications such as system identification, noise cancellation, channel equalization, linear prediction, control, and modeling. In the present book, in order to achieve a global minimum solution to the fitness function related to filter transfer function, biologically inspired algorithm is used. Adaptation to classical Bacterial Foraging Optimization is employed to design stable and optimum digital filter design for signal processing and image processing applications. Bestandsnummer des Verkäufers 9783659434167
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Bacterial Foraging Optimization for Digital Filter Synthesis
Verlag:
LAP LAMBERT Academic Publishing Aug 2013, 2013
ISBN 10: 3659434167
ISBN 13: 9783659434167
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In any deterministic solution, the convergence is not at all guaranteed, whereas, the stochastic and random search algorithms are 1 shot optimization and it can hit the nearly optimized solution, with guarantee. Therefore the AI dependent evolutionary algorithms (GA, PSO, DE, BFOA) are prescribed for this type of optimization problems. Some selected evolutionary algorithms are presented for digital filter design. If the statistical characteristic of the input data varies with respect to time or the required knowledge about input data is not satisfactory, adaptive filters are needed. Adaptive filters (FIR and IIR) have attractive increasing attention due to their widespread use in many different applications such as system identification, noise cancellation, channel equalization, linear prediction, control, and modeling. In the present book, in order to achieve a global minimum solution to the fitness function related to filter transfer function, biologically inspired algorithm is used. Adaptation to classical Bacterial Foraging Optimization is employed to design stable and optimum digital filter design for signal processing and image processing applications.Books on Demand GmbH, Überseering 33, 22297 Hamburg 216 pp. Englisch. Bestandsnummer des Verkäufers 9783659434167
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Bacterial Foraging Optimization for Digital Filter Synthesis
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
ISBN 10: 3659434167
ISBN 13: 9783659434167
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Zustand: New. pp. 216. Bestandsnummer des Verkäufers 26128814992
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Bacterial Foraging Optimization for Digital Filter Synthesis
Verlag:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
ISBN 10: 3659434167
ISBN 13: 9783659434167
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Softcover
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Zustand: New. PRINT ON DEMAND pp. 216. Bestandsnummer des Verkäufers 18128815002
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Bacterial Foraging Optimization for Digital Filter Synthesis
Verlag:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
ISBN 10: 3659434167
ISBN 13: 9783659434167
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Softcover
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Zustand: New. Print on Demand pp. 216 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Bestandsnummer des Verkäufers 131739727
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