ISBN: 9786200007841 - spiking neural network and image processing (7 resultados)

Paperback. Condición: Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock.

Taschenbuch. Condición: Neu. Spiking Neural Network and Image Processing | Soni Adit Chaturvedi (u. a.) | Taschenbuch | 76 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200007841 | 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. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In today's world image recognition by the computer is the most concern issue. Recognition of handwriting has become very useful to make the machine learn to interact between human and computer . For pattern classification and recognition ,Neural Networks are the most powerful tools. This book depicts the strategies for hand written English characters (upper and lowercase) .We focus on classification and recognition based on Leaky-Integrate-and fire neuron model and Izhikevich neuron model which are Spiking Neural Network models.This book illustrates about the simulation of Leaky integrate and fire neuron model and Izhikevich neuron model ,and the results are compared in terms of accuracy, simulation time and firing rates for analysis with some further improvements.The successful simulation of few SNN models like LIF model and Izhikevich model for implementing an algorithm as a pattern classifier for English alphabet have been discussed . We report on advantages of SNN such as Mathematical model computation, High Accuracy, Low Power,Less Area, Useful for real time applications for further enhancement and improvement in terms of cost effectiveness. 76 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In today's world image recognition by the computer is the most concern issue. Recognition of handwriting has become very useful to make the machine learn to interact between human and computer . For pattern classification and recognition ,Neural Networks are the most powerful tools. This book depicts the strategies for hand written English characters (upper and lowercase) .We focus on classification and recognition based on Leaky-Integrate-and fire neuron model and Izhikevich neuron model which are Spiking Neural Network models.This book illustrates about the simulation of Leaky integrate and fire neuron model and Izhikevich neuron model ,and the results are compared in terms of accuracy, simulation time and firing rates for analysis with some further improvements.The successful simulation of few SNN models like LIF model and Izhikevich model for implementing an algorithm as a pattern classifier for English alphabet have been discussed . We report on advantages of SNN such as Mathematical model computation, High Accuracy, Low Power,Less Area, Useful for real time applications for further enhancement and improvement in terms of cost effectiveness.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chaturvedi Soni AditSoni Adit Chaturvedi is Ph.D[ Electronics Engineering] M.Tech (Electronics) and B.E.( E &C) Currently working as Associate Professor and Head in E &C Engg. Deptt., PIET,Nagpur. She has a total teaching experience .…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In today's world image recognition by the computer is the most concern issue. Recognition of handwriting has become very useful to make the machine learn to interact between human and computer . For pattern classification and recognition ,Neural Networks are the most powerful tools. This book depicts the strategies for hand written English characters (upper and lowercase) .We focus on classification and recognition based on Leaky-Integrate-and fire neuron model and Izhikevich neuron model which are Spiking Neural Network models.This book illustrates about the simulation of Leaky integrate and fire neuron model and Izhikevich neuron model ,and the results are compared in terms of accuracy, simulation time and firing rates for analysis with some further improvements.The successful simulation of few SNN models like LIF model and Izhikevich model for implementing an algorithm as a pattern classifier for English alphabet have been discussed . We report on advantages of SNN such as Mathematical model computation, High Accuracy, Low Power,Less Area, Useful for real time applications for further enhancement and improvement in terms of cost effectiveness.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.…