Data Fusion: Concepts and Ideas [electronic resource] /by H B Mitchell.
by Mitchell, H B [author.]; SpringerLink (Online service).
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BookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.Edition: 2nd ed. 2012.Description: XIV, 346p. online resource.ISBN: 9783642272226.Subject(s): Engineering | Electronics | Engineering | Signal, Image and Speech Processing | Computational Intelligence | Electronics and Microelectronics, InstrumentationDDC classification: 621.382 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| TA1637-1638 (Browse shelf) | Available | ||||
| TK7882.S65 (Browse shelf) | Available | ||||
| Long Loan | MAIN LIBRARY | TK5102.9 (Browse shelf) | Available |
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| TK7882.S65 A Perspective on Stereophonic Acoustic Echo Cancellation | TK7882.S65 Speech Enhancement in the STFT Domain | TK7882.S65 Speaker Authentication | TK7882.S65 Data Fusion: Concepts and Ideas | TK7882.S65 Subjective Quality Measurement of Speech | TK7882.S65 Signal Conditioning | TK7882.S65 Quantifying Quality Aspects of Multimodal Interactive Systems |
Introduction -- Sensors -- Architecture -- Common Representational Format -- Spatial Alignment -- Temporal Alignment -- Semantic Alignment -- Radiometric Normalization -- Bayesian Inference -- Parameter Estimation -- Robust Statistics -- Sequential Bayesian Inference -- Bayesian Decision Theory -- Ensemble Learning -- Sensor Management.
“Data Fusion: Concepts and Ideas” provides a comprehensive introduction to the concepts and idea of multisensor data fusion. This textbook is an extensively revised second edition of the author's successful book: "Multi-Sensor Data Fusion: An Introduction". The book is self-contained and no previous knowledge of multi-sensor data fusion is assumed. The reader is made familiar with tools taken from a wide range of diverse subjects including: neural networks, signal processing, statistical estimation, tracking algorithms, computer vision and control theory which are combined by using a common statistical framework. As a consequence, the underlying pattern of relationships that exists between the different methodologies is made evident. The book is illustrated with many real-life examples taken from a diverse range of applications and contains an extensive list of modern references. The new completely revised and updated edition includes nearly 70 pages of new material including a full new chapter as well as approximately 30 new sections, 50 new examples and 100 new references as well as additional Matlab code where appropriate.
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