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Wavelets in Engineering Applications（簡體書）
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商品簡介
《Wavelets in Engineering Applications》收集了作者所研究的小波理論在信息技術中的工程應用的十多篇論文的系統化合集。書中首先介紹了小波變換的基本原理及在信號處理應用中的特性，并在如下應用領域：系統建模、狀態監控、過程控制、振動分析、音頻編碼、圖像質量測量、圖像降噪、無線定位、電力線通信等，分章節詳細的闡述小波理論及其在相關領域的工程實際應用，對各種小波變換形式的優缺點展開細致的論述，并針對相應的工程實例，開發出既能滿足運算精度要求，又能實現快速實時處理的小波技術的工程應用。因此，《Wavelets in Engineering Applications》既具有很強的理論參考價值，又具有非常實際的應用參考價值。
目次
PREFACE
Chapter 1 WAVELET TRANSFORMS IN SIGNAL PROCESSING.
1.1 Introduction
1.2 The continuous wavelet transform
1.3 The discrete wavelet transform
1.4 The heisenberg uncertainty principle and time-frequency decompositions
1.5 Multi-resolution analysis
1.6 Some important properties of wavelets
1.6.1 Compact support
1.6.2 Rational coefficients
1.6.3 Symmetry
1.6.4 Smoothness
1.6.5 Number of vanishing moments
1.6.6 Analytic expression
1.7 Current fast WT algorithms PREFACE
Chapter 1 WAVELET TRANSFORMS IN SIGNAL PROCESSING.
1.1 Introduction
1.2 The continuous wavelet transform
1.3 The discrete wavelet transform
1.4 The heisenberg uncertainty principle and time-frequency decompositions
1.5 Multi-resolution analysis
1.6 Some important properties of wavelets
1.6.1 Compact support
1.6.2 Rational coefficients
1.6.3 Symmetry
1.6.4 Smoothness
1.6.5 Number of vanishing moments
1.6.6 Analytic expression
1.7 Current fast WT algorithms
1.7.1 Orthogonal wavelets
1.7.2 Semiorthogonal (nonorthogonal) wavelets
1.7.3 Biorthogonal wavelets
1.7.4 Wavelet packets
1.7.5 Harmonic wavelets
1.8 Discussion
REFERENCES
Chapter 2 SYSTEM MODELLING
2.1 Introduction
2.2 The underlying principle of Fourier harmonic analysis
2.3 Autocorrelation wavelet algorithm
2.4 Vibration model selection with FT and autocorrelation wavelet algorithm
2.5 Coefficients estimation with least-squares algorithm
2.6 Results and discussion
2.7 Condition monitoring of bearing
2.8 Concluding remarks
REFERENCES
Chapter 3 CONDITION MONITORING
3.1 Wavelet analysis
3.2 Filter design and fast continuous wavelet algorithm
3.3 Small defect detection of bearing
3.3.1 Specific frequency ranges monitoring
3.3.2 Significant and natural frequencies monitoring
3.4 Concluding remarks
REFERENCES
Chapter 4 PROCESS CONTROL
4.1 Introduction
4.2 Vibration and surface quality
4.2.1 Theoretical calculation of surface quality
4.2.2 Vibration during machining
4.3 Adaptive spline wavelet algorithm
4.3.1 Battle-Lemarid wavelet filter design
4.3.2 Arbitrary fine time-scale representation
4.3.3 Adaptive frequency resolution decomposition
4.4 Methodology of experiment
4.5 Results and discussions
4.5.1 Experimental results
4.5.2 Discussions
4.6 Concluding remarks
REFERENCES
Chapter 5 VIBRATION ANALYSIS
5.1 Introduction
5.2 Machining process vibration
5.3 Wavelet algorithm with cross-correlation
5.4 Experimental set-up
5.5 Experimental results
5.6 Discussion
5.7 Concluding remarks
REFERENCES
Chapter 6 AUDIO CODING
6.1 Introduction
6.2 DSP Implantation of lifting wavelet transform
6.3 Embedded coding and error resilience
6.4 Results of experiment and simulation
6.5 Conclusions
REFERENCES
Chapter 7 IMAGE QUALITY MEASUREMENT
7.1 Introduction
7.2 Wavelet analysis and the lifting scheme
7.3 Image quality evaluation
7.3.1 Image noise analysis
7.3.2 Image sharpness analysis
7.3.3 Image brightness analysis
7.3.4 Image contrast analysis
7.3.5 Image MTF analysis
7.3.6 Image quality quantification and classification
7.3.7 Optimisation of weighting coefficients
7.4 Experimental results and discussions
7.5 Conclusions
REFERENCES
Chapter 8 IMAGE DENOISING
8.1 Introduction
8.2 Fast lifting wavelet analysis
8.3 Noise reduction with wavelet thresholding and derivative filtering
8.3.1 General noise reduction
8.3.2 Fine noise reduction
8.4 Experimental results and discussions
8.5 Conclusions
REFERENCES
Chapter 9 WIRELESS POSITIONING
9.1 Introduction
9.2 Wavelet notch filter design
9.3 System model and narrowband interference detection
9.4 Experimental results and discussions
9.5 Conclusions
REFERENCES
Chapter 10 POWER LINE COMMUNICATIONS
10.1 Introduction
10.2 Multicarrier spread spectrum system
10.3 Carrier frequency error estimation and compensation
10.4 Time-frequency analysis of noise
10.5 Noise detection and filtering
10.6 Experimental results and discussions
10.7 Conclusions
REFERENCES
Chapter 1 WAVELET TRANSFORMS IN SIGNAL PROCESSING.
1.1 Introduction
1.2 The continuous wavelet transform
1.3 The discrete wavelet transform
1.4 The heisenberg uncertainty principle and time-frequency decompositions
1.5 Multi-resolution analysis
1.6 Some important properties of wavelets
1.6.1 Compact support
1.6.2 Rational coefficients
1.6.3 Symmetry
1.6.4 Smoothness
1.6.5 Number of vanishing moments
1.6.6 Analytic expression
1.7 Current fast WT algorithms PREFACE
Chapter 1 WAVELET TRANSFORMS IN SIGNAL PROCESSING.
1.1 Introduction
1.2 The continuous wavelet transform
1.3 The discrete wavelet transform
1.4 The heisenberg uncertainty principle and time-frequency decompositions
1.5 Multi-resolution analysis
1.6 Some important properties of wavelets
1.6.1 Compact support
1.6.2 Rational coefficients
1.6.3 Symmetry
1.6.4 Smoothness
1.6.5 Number of vanishing moments
1.6.6 Analytic expression
1.7 Current fast WT algorithms
1.7.1 Orthogonal wavelets
1.7.2 Semiorthogonal (nonorthogonal) wavelets
1.7.3 Biorthogonal wavelets
1.7.4 Wavelet packets
1.7.5 Harmonic wavelets
1.8 Discussion
REFERENCES
Chapter 2 SYSTEM MODELLING
2.1 Introduction
2.2 The underlying principle of Fourier harmonic analysis
2.3 Autocorrelation wavelet algorithm
2.4 Vibration model selection with FT and autocorrelation wavelet algorithm
2.5 Coefficients estimation with least-squares algorithm
2.6 Results and discussion
2.7 Condition monitoring of bearing
2.8 Concluding remarks
REFERENCES
Chapter 3 CONDITION MONITORING
3.1 Wavelet analysis
3.2 Filter design and fast continuous wavelet algorithm
3.3 Small defect detection of bearing
3.3.1 Specific frequency ranges monitoring
3.3.2 Significant and natural frequencies monitoring
3.4 Concluding remarks
REFERENCES
Chapter 4 PROCESS CONTROL
4.1 Introduction
4.2 Vibration and surface quality
4.2.1 Theoretical calculation of surface quality
4.2.2 Vibration during machining
4.3 Adaptive spline wavelet algorithm
4.3.1 Battle-Lemarid wavelet filter design
4.3.2 Arbitrary fine time-scale representation
4.3.3 Adaptive frequency resolution decomposition
4.4 Methodology of experiment
4.5 Results and discussions
4.5.1 Experimental results
4.5.2 Discussions
4.6 Concluding remarks
REFERENCES
Chapter 5 VIBRATION ANALYSIS
5.1 Introduction
5.2 Machining process vibration
5.3 Wavelet algorithm with cross-correlation
5.4 Experimental set-up
5.5 Experimental results
5.6 Discussion
5.7 Concluding remarks
REFERENCES
Chapter 6 AUDIO CODING
6.1 Introduction
6.2 DSP Implantation of lifting wavelet transform
6.3 Embedded coding and error resilience
6.4 Results of experiment and simulation
6.5 Conclusions
REFERENCES
Chapter 7 IMAGE QUALITY MEASUREMENT
7.1 Introduction
7.2 Wavelet analysis and the lifting scheme
7.3 Image quality evaluation
7.3.1 Image noise analysis
7.3.2 Image sharpness analysis
7.3.3 Image brightness analysis
7.3.4 Image contrast analysis
7.3.5 Image MTF analysis
7.3.6 Image quality quantification and classification
7.3.7 Optimisation of weighting coefficients
7.4 Experimental results and discussions
7.5 Conclusions
REFERENCES
Chapter 8 IMAGE DENOISING
8.1 Introduction
8.2 Fast lifting wavelet analysis
8.3 Noise reduction with wavelet thresholding and derivative filtering
8.3.1 General noise reduction
8.3.2 Fine noise reduction
8.4 Experimental results and discussions
8.5 Conclusions
REFERENCES
Chapter 9 WIRELESS POSITIONING
9.1 Introduction
9.2 Wavelet notch filter design
9.3 System model and narrowband interference detection
9.4 Experimental results and discussions
9.5 Conclusions
REFERENCES
Chapter 10 POWER LINE COMMUNICATIONS
10.1 Introduction
10.2 Multicarrier spread spectrum system
10.3 Carrier frequency error estimation and compensation
10.4 Time-frequency analysis of noise
10.5 Noise detection and filtering
10.6 Experimental results and discussions
10.7 Conclusions
REFERENCES
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