Predictive Artificial Neural Networks: A Block-adaptive Scheme for Lossless Telemetry Data Compression - Brossura
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Data compression deals with removal of redundancy, reducing bandwidth and thus lowering transmission and storage costs. Telemetry data can be sensitive to inaccuracies and require lossless compression for exact reconstruction at the receiver. One technology that has been successfully applied in a wide range of applications is artificial neural networks (ANN), a massively parallel system with pattern recognition capabilities. This monograph is a reproduction of the author?s postgraduate thesis work at Multimedia University, Malaysia. A two-stage predictor-encoder combination is proposed, incorporating a variety of feedforward, recurrent and radial basis ANN architectures, as the predictors. The encoders are well known compression algorithms. Characteristic features of the models, transmission issues and other practical considerations are taken into account to determine optimised configuration of the schemes. Significant compression results are reported, along with a critical review of the strengths and weaknesses of over 50 implementations simulated with satellite telemetry data.
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Predictive Artificial Neural Networks
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LAP LAMBERT Academic Publishing Jan 2010, 2010
ISBN 10: 3838337441
ISBN 13: 9783838337449
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data compression deals with removal of redundancy, reducing bandwidth and thus lowering transmission and storage costs. Telemetry data can be sensitive to inaccuracies and require lossless compression for exact reconstruction at the receiver. One technology that has been successfully applied in a wide range of applications is artificial neural networks (ANN), a massively parallel system with pattern recognition capabilities. This monograph is a reproduction of the author s postgraduate thesis work at Multimedia University, Malaysia. A two-stage predictor-encoder combination is proposed, incorporating a variety of feedforward, recurrent and radial basis ANN architectures, as the predictors. The encoders are well known compression algorithms. Characteristic features of the models, transmission issues and other practical considerations are taken into account to determine optimised configuration of the schemes. Significant compression results are reported, along with a critical review of the strengths and weaknesses of over 50 implementations simulated with satellite telemetry data. 216 pp. Englisch. Codice articolo 9783838337449
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Predictive Artificial Neural Networks
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LAP Lambert Academic Publishing, 2010
ISBN 10: 3838337441
ISBN 13: 9783838337449
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Data compression deals with removal of redundancy, reducing bandwidth and thus lowering transmission and storage costs. Telemetry data can be sensitive to inaccuracies and require lossless compression for exact reconstruction at the receiver. One technology. Codice articolo 5414290
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Predictive Artificial Neural Networks | A Block-adaptive Scheme for Lossless Telemetry Data Compression
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838337441
ISBN 13: 9783838337449
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Taschenbuch. Condizione: Neu. Predictive Artificial Neural Networks | A Block-adaptive Scheme for Lossless Telemetry Data Compression | Rajasvaran Logeswaran | Taschenbuch | 216 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838337449 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 101352855
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Predictive Artificial Neural Networks
Editore:
LAP LAMBERT Academic Publishing Jan 2010, 2010
ISBN 10: 3838337441
ISBN 13: 9783838337449
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data compression deals with removal of redundancy, reducing bandwidth and thus lowering transmission and storage costs. Telemetry data can be sensitive to inaccuracies and require lossless compression for exact reconstruction at the receiver. One technology that has been successfully applied in a wide range of applications is artificial neural networks (ANN), a massively parallel system with pattern recognition capabilities. This monograph is a reproduction of the author''s postgraduate thesis work at Multimedia University, Malaysia. A two-stage predictor-encoder combination is proposed, incorporating a variety of feedforward, recurrent and radial basis ANN architectures, as the predictors. The encoders are well known compression algorithms. Characteristic features of the models, transmission issues and other practical considerations are taken into account to determine optimised configuration of the schemes. Significant compression results are reported, along with a critical review of the strengths and weaknesses of over 50 implementations simulated with satellite telemetry data.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 216 pp. Englisch. Codice articolo 9783838337449
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Predictive Artificial Neural Networks : A Block-adaptive Scheme for Lossless Telemetry Data Compression
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838337441
ISBN 13: 9783838337449
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data compression deals with removal of redundancy, reducing bandwidth and thus lowering transmission and storage costs. Telemetry data can be sensitive to inaccuracies and require lossless compression for exact reconstruction at the receiver. One technology that has been successfully applied in a wide range of applications is artificial neural networks (ANN), a massively parallel system with pattern recognition capabilities. This monograph is a reproduction of the author s postgraduate thesis work at Multimedia University, Malaysia. A two-stage predictor-encoder combination is proposed, incorporating a variety of feedforward, recurrent and radial basis ANN architectures, as the predictors. The encoders are well known compression algorithms. Characteristic features of the models, transmission issues and other practical considerations are taken into account to determine optimised configuration of the schemes. Significant compression results are reported, along with a critical review of the strengths and weaknesses of over 50 implementations simulated with satellite telemetry data. Codice articolo 9783838337449
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Predictive Artificial Neural Networks: A Block-adaptive Scheme for Lossless Telemetry Data Compression
Editore:
LAP Lambert Academic Publishing, 2010
ISBN 10: 3838337441
ISBN 13: 9783838337449
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