小波在工程中的应用

PREFACEChapter 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 REFERENCESChapter 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 REFERENCESChapter 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 REFERENCESChapter 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 REFERENCESChapter 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 REFERENCESChapter 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 REFERENCESChapter 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 REFERENCESChapter 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 REFERENCESChapter 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 REFERENCESChapter 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

《Wavelets in Engineering Applications》由Luo Gaoyong编著。 To assist their understanding the book begins with some standard information about wavelets.This is not intended to be exhaustive but sets the background for the rest of the book.Ideally the reader should have a mathematical background and some prior experience with transforms would be helpful. The following chapters of the book represent nearly 15 years work in which my fascination at the versatility of wavelets has grown.This book is structured so that each chapter can be read separately, depending on the reader's area of interest.