TAILIEUCHUNG - Phân tích tín hiệu P8

Wavelet Transform The wavelettransform was introduced at the beginning of the 1980s by Morlet et al., who used it to evaluate seismic data [l05 ],[106]. Since then, various types of wavelet transforms have been developed, and many other applications ha vebeen found. The continuous-time wavelet transform, also called the integral wavelet transform (IWT), finds most of its applications in data analysis, where it yields an affine invariant time-frequency representation. | Signal Analysis Wavelets Filter Banks Time-Frequency Transforms and Applications. Alfred Mertins Copyright 1999 John Wiley Sons Ltd Print ISBN 0-471-98626-7 Electronic ISBN 0-470-84183-4 Chapter 8 Wavelet Transform The wavelet transform was introduced at the beginning of the 1980s by Morlet et al. who used it to evaluate seismic data 105 106 . Since then various types of wavelet transforms have been developed and many other applications havebeen found. The continuous-time wavelet transform also called the integral wavelet transform IWT finds most of its applications in data analysis where it yields an affine invariant time-frequency representation. The most famous version however is the discrete wavelet transform DWT . This transform has excellent signal compaction properties for many classes of real-world signals while being computationally very efficient. Therefore it has been applied to almost all technical fields including image compression denoising numerical integration and pattern recognition. The Continuous-Time Wavelt Transform The wavelet transform Wx b a of a continuous-time signal x t is defined as Wx b a a -5 i x t ip - - dt. J-oo a Thus the wavelet transform is computed as the inner product of x t and translated and scaled versions of a single function ip f the so-called wavelet. If we consider ip t to be a bandpass impulse response then the wavelet analysis can be understood as a bandpass analysis. By varying the scaling 210 . The Continuous-Time Wavelet Transform 211 parameter a the center frequency and the bandwidth of the bandpass are influenced. The variation of b simply means a translation in time so that for a fixed a the transform can be seen as a convolution of x t with the time-reversed and scaled wavelet Wx t a a _2x t V o i V a i The prefactor a -1 2 is introduced in order to ensure that all scaled functions ữ -1 2 t ữ with a IR have the same energy. Since the analysis function ip t is scaled and not modulated like the .

TỪ KHÓA LIÊN QUAN
TAILIEUCHUNG - Chia sẻ tài liệu không giới hạn
Địa chỉ : 444 Hoang Hoa Tham, Hanoi, Viet Nam
Website : tailieuchung.com
Email : tailieuchung20@gmail.com
Tailieuchung.com là thư viện tài liệu trực tuyến, nơi chia sẽ trao đổi hàng triệu tài liệu như luận văn đồ án, sách, giáo trình, đề thi.
Chúng tôi không chịu trách nhiệm liên quan đến các vấn đề bản quyền nội dung tài liệu được thành viên tự nguyện đăng tải lên, nếu phát hiện thấy tài liệu xấu hoặc tài liệu có bản quyền xin hãy email cho chúng tôi.
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.