Exploiting Covariance Structure for Signal Detection in Array Processing
Perry, Perry
ISBN 10: 3384276647 ISBN 13: 9783384276643
Published by Tredition Gmbh, 2024
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Array processing involves utilizing multiple sensors (e.g., antennas) to collect data from a spatial environment. The primary objective is to extract the desired signal from a mixture of noise and interference. Several techniques exist for signal detection, including beamforming, matched filtering, and likelihood ratio tests. These methods typically rely on assumptions about the signal and noise characteristics. However, real-world environments often violate these assumptions. Noise may not be purely white (uncorrelated) and can exhibit spatial coherence. Additionally, interference might be structured and non-stationary. Here's where exploiting the covariance structure of the received data becomes advantageous.
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Title: Exploiting Covariance Structure for Signal ...
Publisher: Tredition Gmbh
Publication Date: 2024
Binding: Soft cover
Condition: New
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ISBN 10: 3384276647
ISBN 13: 9783384276643
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Paperback or Softback. Condition: New. Exploiting Covariance Structure for Signal Detection in Array Processing 0.37. Book. Seller Inventory # BBS-9783384276643
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Exploiting Covariance Structure for Signal Detection in Array Processing
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Taschenbuch. Condition: Neu. Neuware -Array processing involves utilizing multiple sensors (e.g., antennas) to collect data from a spatial environment. The primary objective is to extract the desired signal from a mixture of noise and interference. Several techniques exist for signal detection, including beamforming, matched filtering, and likelihood ratio tests. These methods typically rely on assumptions about the signal and noise characteristics.However, real-world environments often violate these assumptions. Noise may not be purely white (uncorrelated) and can exhibit spatial coherence. Additionally, interference might be structured and non-stationary. Here's where exploiting the covariance structure of the received data becomes advantageous.tredition GmbH, Heinz-Beusen-Stieg 5, 22926 Ahrensburg 108 pp. Englisch. Seller Inventory # 9783384276643
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Exploiting Covariance Structure for Signal Detection in Array Processing
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Taschenbuch. Condition: Neu. Exploiting Covariance Structure for Signal Detection in Array Processing | Perry | Taschenbuch | Englisch | 2024 | tredition | EAN 9783384276643 | Verantwortliche Person für die EU: tredition GmbH, Heinz-Beusen-Stieg 5, 22926 Ahrensburg, support[at]tredition[dot]com | Anbieter: preigu. Seller Inventory # 129562977
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Exploiting Covariance Structure for Signal Detection in Array Processing
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Array processing involves utilizing multiple sensors (e.g., antennas) to collect data from a spatial environment. The primary objective is to extract the desired signal from a mixture of noise and interference. Several techniques exist for signal detection, including beamforming, matched filtering, and likelihood ratio tests. These methods typically rely on assumptions about the signal and noise characteristics.However, real-world environments often violate these assumptions. Noise may not be purely white (uncorrelated) and can exhibit spatial coherence. Additionally, interference might be structured and non-stationary. Here's where exploiting the covariance structure of the received data becomes advantageous. 108 pp. Englisch. Seller Inventory # 9783384276643
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Exploiting Covariance Structure for Signal Detection in Array Processing
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Array processing involves utilizing multiple sensors (e.g., antennas) to collect data from a spatial environment. The primary objective is to extract the desired signal from a mixture of noise and interference. Several techniques exist for signal detection, including beamforming, matched filtering, and likelihood ratio tests. These methods typically rely on assumptions about the signal and noise characteristics.However, real-world environments often violate these assumptions. Noise may not be purely white (uncorrelated) and can exhibit spatial coherence. Additionally, interference might be structured and non-stationary. Here's where exploiting the covariance structure of the received data becomes advantageous. Seller Inventory # 9783384276643
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Exploiting Covariance Structure for Signal Detection in Array Processing (Paperback)
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Paperback. Condition: new. Paperback. Array processing involves utilizing multiple sensors (e.g., antennas) to collect data from a spatial environment. The primary objective is to extract the desired signal from a mixture of noise and interference. Several techniques exist for signal detection, including beamforming, matched filtering, and likelihood ratio tests. These methods typically rely on assumptions about the signal and noise characteristics. However, real-world environments often violate these assumptions. Noise may not be purely white (uncorrelated) and can exhibit spatial coherence. Additionally, interference might be structured and non-stationary. Here's where exploiting the covariance structure of the received data becomes advantageous. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9783384276643
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