The Resource Sparse representations for radar with MATLAB examples, Peter Knee, (electronic book)
Sparse representations for radar with MATLAB examples, Peter Knee, (electronic book)
Resource Information
The item Sparse representations for radar with MATLAB examples, Peter Knee, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Sydney Jones Library, University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item Sparse representations for radar with MATLAB examples, Peter Knee, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Sydney Jones Library, University of Liverpool.
This item is available to borrow from 1 library branch.
- Summary
- Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB examples to emphasize the practical implementations both inside and outside the radar field
- Language
- eng
- Extent
- 1 electronic text (xiii, 71 p.)
- Contents
-
- List of symbols -- List of acronyms -- Acknowledgments --
- 1. Radar systems: a signal processing perspective -- 1.1 History of radar -- 1.2 Current radar applications -- 1.3 Basic organization --
- 2. Introduction to sparse representations -- 2.1 Signal coding using sparse representations -- 2.2 Geometric interpretation -- 2.3 Sparse recovery algorithms -- 2.3.1 Convex optimization -- 2.3.2 Greedy approach -- 2.4 Examples -- 2.4.1 Non-uniform sampling -- 2.4.2 Image reconstruction from Fourier sampling --
- 3. Dimensionality reduction -- 3.1 Linear dimensionality reduction techniques -- 3.1.1 Principal component analysis (PCA) and multidimensional scaling (MDS) -- 3.1.2 Linear discriminant analysis (LDA) -- 3.2 Nonlinear dimensionality reduction techniques -- 3.2.1 ISOMAP -- 3.2.2 Local linear embedding (LLE) -- 3.2.3 Linear model alignment -- 3.3 Random projections --
- 4. Radar signal processing fundamentals -- 4.1 Elements of a pulsed radar -- 4.2 Range and angular resolution -- 4.3 Imaging -- 4.4 Detection --
- 5. Sparse representations in radar -- 5.1 Echo signal detection and image formation -- 5.2 Angle-Doppler-range estimation -- 5.3 Image registration (matching) and change detection for SAR -- 5.4 Automatic target classification -- 5.4.1 Sparse representation for target classification -- 5.4.2 Sparse representation-based spatial pyramids --
- A. Code sample -- Non-uniform sampling and signal reconstruction code -- Long-Shepp phantom test image reconstruction code -- Signal bandwidth code -- Bibliography -- Author's biography
- Isbn
- 9781627050357
- Label
- Sparse representations for radar with MATLAB examples
- Title
- Sparse representations for radar with MATLAB examples
- Statement of responsibility
- Peter Knee
- Language
- eng
- Summary
- Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB examples to emphasize the practical implementations both inside and outside the radar field
- Cataloging source
- CaBNVSL
- http://library.link/vocab/creatorName
- Knee, Peter
- Dewey number
- 621.3848
- Illustrations
- illustrations
- Index
- no index present
- LC call number
- TK6578
- LC item number
- .K547 2012
- Literary form
- non fiction
- Nature of contents
-
- abstracts summaries
- bibliography
- http://library.link/vocab/subjectName
-
- Radar
- Signal processing
- Target audience
- specialized
- Label
- Sparse representations for radar with MATLAB examples, Peter Knee, (electronic book)
- Bibliography note
- Includes bibliographical references (p. 63-69)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- List of symbols -- List of acronyms -- Acknowledgments --
- 1. Radar systems: a signal processing perspective -- 1.1 History of radar -- 1.2 Current radar applications -- 1.3 Basic organization --
- 2. Introduction to sparse representations -- 2.1 Signal coding using sparse representations -- 2.2 Geometric interpretation -- 2.3 Sparse recovery algorithms -- 2.3.1 Convex optimization -- 2.3.2 Greedy approach -- 2.4 Examples -- 2.4.1 Non-uniform sampling -- 2.4.2 Image reconstruction from Fourier sampling --
- 3. Dimensionality reduction -- 3.1 Linear dimensionality reduction techniques -- 3.1.1 Principal component analysis (PCA) and multidimensional scaling (MDS) -- 3.1.2 Linear discriminant analysis (LDA) -- 3.2 Nonlinear dimensionality reduction techniques -- 3.2.1 ISOMAP -- 3.2.2 Local linear embedding (LLE) -- 3.2.3 Linear model alignment -- 3.3 Random projections --
- 4. Radar signal processing fundamentals -- 4.1 Elements of a pulsed radar -- 4.2 Range and angular resolution -- 4.3 Imaging -- 4.4 Detection --
- 5. Sparse representations in radar -- 5.1 Echo signal detection and image formation -- 5.2 Angle-Doppler-range estimation -- 5.3 Image registration (matching) and change detection for SAR -- 5.4 Automatic target classification -- 5.4.1 Sparse representation for target classification -- 5.4.2 Sparse representation-based spatial pyramids --
- A. Code sample -- Non-uniform sampling and signal reconstruction code -- Long-Shepp phantom test image reconstruction code -- Signal bandwidth code -- Bibliography -- Author's biography
- Control code
- 201208ASE010
- Dimensions
- unknown
- Extent
- 1 electronic text (xiii, 71 p.)
- File format
- multiple file formats
- Form of item
- online
- Isbn
- 9781627050357
- Issn
- 1938-1735
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- ill., digital file.
- Reformatting quality
- access
- Specific material designation
- remote
- Label
- Sparse representations for radar with MATLAB examples, Peter Knee, (electronic book)
- Bibliography note
- Includes bibliographical references (p. 63-69)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- List of symbols -- List of acronyms -- Acknowledgments --
- 1. Radar systems: a signal processing perspective -- 1.1 History of radar -- 1.2 Current radar applications -- 1.3 Basic organization --
- 2. Introduction to sparse representations -- 2.1 Signal coding using sparse representations -- 2.2 Geometric interpretation -- 2.3 Sparse recovery algorithms -- 2.3.1 Convex optimization -- 2.3.2 Greedy approach -- 2.4 Examples -- 2.4.1 Non-uniform sampling -- 2.4.2 Image reconstruction from Fourier sampling --
- 3. Dimensionality reduction -- 3.1 Linear dimensionality reduction techniques -- 3.1.1 Principal component analysis (PCA) and multidimensional scaling (MDS) -- 3.1.2 Linear discriminant analysis (LDA) -- 3.2 Nonlinear dimensionality reduction techniques -- 3.2.1 ISOMAP -- 3.2.2 Local linear embedding (LLE) -- 3.2.3 Linear model alignment -- 3.3 Random projections --
- 4. Radar signal processing fundamentals -- 4.1 Elements of a pulsed radar -- 4.2 Range and angular resolution -- 4.3 Imaging -- 4.4 Detection --
- 5. Sparse representations in radar -- 5.1 Echo signal detection and image formation -- 5.2 Angle-Doppler-range estimation -- 5.3 Image registration (matching) and change detection for SAR -- 5.4 Automatic target classification -- 5.4.1 Sparse representation for target classification -- 5.4.2 Sparse representation-based spatial pyramids --
- A. Code sample -- Non-uniform sampling and signal reconstruction code -- Long-Shepp phantom test image reconstruction code -- Signal bandwidth code -- Bibliography -- Author's biography
- Control code
- 201208ASE010
- Dimensions
- unknown
- Extent
- 1 electronic text (xiii, 71 p.)
- File format
- multiple file formats
- Form of item
- online
- Isbn
- 9781627050357
- Issn
- 1938-1735
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- ill., digital file.
- Reformatting quality
- access
- Specific material designation
- remote
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Sparse-representations-for-radar-with-MATLAB/CIIULbRz60A/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Sparse-representations-for-radar-with-MATLAB/CIIULbRz60A/">Sparse representations for radar with MATLAB examples, Peter Knee, (electronic book)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">Sydney Jones Library, University of Liverpool</a></span></span></span></span></div>
