Rahul kumar sahu (5 Ergebnisse)

Taschenbuch. Zustand: Neu. Design And Analysis Of A Low Pass FIR Filter Using Genetic Algorithm | Using Mean Square Error Approach | Rahul Kumar Sahu (u. a.) | Taschenbuch | 88 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659786655 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Genetic Algorithm (GA) is a computational evolutionary search technique which is based on Darwin's theory of natural selection i.e. 'best fittest will survive'. The advantage of Evolutionary algorithm is it searches a population of points in parallel, not a single point. GA has been used for the designing & analysis of Finite Impulse Response (FIR) Low Pass Filter (LPF) by optimizes the error function i.e. Mean Square Error (MSE). In this the coefficients of the filter are treated as chromosomes which are optimized by the Genetic Algorithm to obtain a filter that would satisfy prescribed specifications and also reduces the multipliers and adders of the FIR filter making the system cost effective. After designing of FIR low pass digital filter, it is also compared with other designing methods viz. Equiripple, Least Square, Window techniques and Parks-McClellan Algorithm; to verify the improved accuracy in terms of transition width and reduced side lobes. 88 pp. Englisch.…

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sahu Rahul KumarRahul Kumar Sahu received his B.Tech. Degree in Electronics and Communication Engineering from Gautam Buddh Technical University,Uttar Pradesh, India in 2011 and Master of Engineering in Communication Control and Netw.…

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Genetic Algorithm (GA) is a computational evolutionary search technique which is based on Darwin's theory of natural selection i.e. 'best fittest will survive'. The advantage of Evolutionary algorithm is it searches a population of points in parallel, not a single point. GA has been used for the designing & analysis of Finite Impulse Response (FIR) Low Pass Filter (LPF) by optimizes the error function i.e. Mean Square Error (MSE). In this the coefficients of the filter are treated as chromosomes which are optimized by the Genetic Algorithm to obtain a filter that would satisfy prescribed specifications and also reduces the multipliers and adders of the FIR filter making the system cost effective. After designing of FIR low pass digital filter, it is also compared with other designing methods viz. Equiripple, Least Square, Window techniques and Parks-McClellan Algorithm; to verify the improved accuracy in terms of transition width and reduced side lobes.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.…