Trực quan wavelets

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  • Intuitive Introduction to Wavelets 2.1 TECHNICAL HISTORY AND BACKGROUND The first questions from those curious about wavelets are: What is a wavelet? Who invented wavelets? What can one gain by using wavelets? 2.1.1 Historical Development Wavelets are sometimes referred to as the twentieth-century Fourier analysis. Wavelets exploit the multiresolution analysis just like microscopes do in microbiology. The genesis of wavelets began in 1910 when A. Haar proposed the staircase approximation to approximate a function, using the piecewise constants now called the Haar wavelets [1]....

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  • Canonical Multiwavelets As discussed in the previous chapters, wavelets have provided many beneficial features, including orthogonality, vanishing moments, regularity (continuity and smoothness), multiresolution analysis, among these features. Some wavelets are compactly supported in the time domain (Coifman, Daubechies) or in the frequency domain (Meyer), and some are symmetrical (Haar, Battle–Lemarie). On many occasions it would be very useful if the basis functions were symmetrical.

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  • Wavelets in Scattering and Radiation In this chapter we examine scattering from 2D grooves using standard Coiflets, scattering from 2D and 3D objects, scattering and radiation of curved wire antennas, and scatterers employing Coifman intervallic wavelets. We provide the error estimate and convergence rate of the single-point quadrature formula based on Coifman scalets. We also introduce the smooth local cosine (SLC), which is referred to as the Malvar wavelet [1], as an alternative to the intervallic wavelets in handling bounded intervals. 7.

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  • Basic Orthogonal Wavelet Theory In Chapter 2 we saw how multiresolution analysis (MRA) works for the Haar system. A signal was decomposed into many components on different resolution levels. These components are mutually orthogonal. Despite their attractiveness, the Haar scalets and wavelets are not continuous functions. The discontinuities can create problems when applied to physical modeling. In this chapter we will construct many other orthogonal wavelets that are continuous and may even be smooth functions. ...

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  • Wavelets in Boundary Integral Equations Numerical treatment of integral equations can be found in classic books [1, 2]. In this chapter the integral equations obtained from field analysis of electromagnetic wave scattering, radiating, and guiding problems are solved by the wavelet expansion method [3–7]. The integral equations are converted into a system of linear algebraic equations. The subsectional bases, namely the pulses or piecewise sinusoidal (PWS) modes, are replaced by a set of orthogonal wavelets.

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  • Wavelets in Rough Surface Scattering In this chapter we will study scattering of electromagnetic waves from rough surfaces numerically, using the Coifman wavelets. Owing to the orthogonality, vanishing moments, and multiresolution analysis, a very sparse moment matrix is obtained. In addition the wavelet bases are continuous. Hence the sampling rate for wavelet bases is reduced to one-half the rate of the pulse cases, allowing the same computer resource to deal with quadruple the truncated surface area.

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  • Wavelets in Packaging, Interconnects, and EMC In this chapter we will study multiconductor, multilayered transmission lines (MMTL) employing quasi-static, quasi-dynamic, and full-wave analyses. We extract from MMTL the distributed (parasitic) parameters in matrix form of the capacitance [C], inductance [L], resistance [R] and conductance [G], or the [Z ]-parameters, [Y ]-parameters, or more generally the scattering matrix [S].

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  • Wavelets in Nonlinear Semiconductor Devices Semiconductor device behavior can be described by a system of coupled partial differential equations (PDEs) with associated boundary conditions, requiring the conservation of charge and energy. In physics one is more interested in the quantities of charge concentration, average velocity, and mean energy, for example. From an engineering standpoint, potential, fields, current, and I -V curves are the desired parameters.

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  • Tài liệu “Công cụ phân tích Wavelet và ứng dụng trong Matlab” được biên soạn với nội dung là toàn bộ các ví dụ trực quan và thực tế giúp cho bạn đọc có khả năng hiểu rõ được mọi vấn đề cơ bản của Wavelet hiện nay và đặc biệt là cung cấp ý tưởng để ứng dụng Wavelet vào thực tế

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  • Notations and Mathematical Preliminaries 1.1 NOTATIONS AND ABBREVIATIONS The notations and abbreviations used in the book are summarized here for ease of reference. D (α) f = f α (t) := d f α (t)/dt α f¯—complex conjugate of f ∞ fˆ := −∞ f (t)e−iωt dt, Fourier transform of f (t) ∞ 1 f (t) := 2π −∞ fˆ(ω)eiωt dω, inverse Fourier transform of fˆ(ω) f —norm of a function f ∗ g—convolution f, h := f (t)h(t) dt, inner product f n = O(n)-order of n, ∃C such that f n ≤ Cn C—complex N —nonnegative integers R—real number...

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  • Sampling Biorthogonal Time Domain Method (SBTD) The finite difference time domain (FDTD) method was proposed by K. Yee [1] in 1966. The simplicity of the FDTD method in mathematics has proved to be its great advantage. The method does not involve any integral equations, Green’s functions, singularities, nor matrix equations. Neither does it involve functional or variational principles. In addition the FDTD proves to be versatile when used in complicated geometries.

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  • Hiện nay xử lý tín hiệu đang là một vấn đề được quan tâm và ứng dụng rộng rãi trong nhiều ngành khoa học và kỹ thuật như: điện, điện tử, tự động hóa, viễn thông, tin học... Trong thực tế, các tín hiệu được đo trong miền thời gian hoặc không gian. Nghĩa là tín hiệu là một hàm theo biến thời gian hoặc không gian. Khảo sát tín hiệu trực tiếp trong miền thời gian (không gian) đôi khi gặp phải những khó khăn nhất định...

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  • Những quan tâm chính trong thời gian gần đây là việc phát triển các kỹ thuật biến đổi mới. Nhận biết địa chỉ các vấn đề đối với việc nén ảnh, các cạnh và các đặc trưng cần nhận biết khác, cũng như việc phân tích cấu trúc ảnh. Các kỹ thuật được biết đến như phân tích đa giải pháp, phân tích phổ thời gian, thuật toán hình chóp, và biến đổi sóng con (Wavelet).

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  • Đồ án tốt nghiệp..GVHD : ThS. Võ Thị Hương..Giải pháp cung cấp dịch vụ IPTV.của Công ty VTC Digicom.GVHD: Võ Thị Hƣơng.Sinh viên: Hồ Anh Quân.Lớp:.09 LTDT..SVTH : Hồ Anh Quân..Trang II..09LTDT...Đồ án tốt nghiệp..GVHD : ThS. Võ Thị Hương..MỤC LỤC.Trang.MỤC LỤC ..…………………….…………………………..………..I.DANH MỤC TỪ VIẾT TẮT……………………………................III.LỜI MỞ ĐẦU …………………..………………………................ V.CHƢƠNG 1 : TỔNG QUAN VỀ HỆ THỐNG CUNG CẤP DỊCH VỤ IPTV.1.1.Giới thiệu chƣơng ….......……………………………………….1.1.2 Khái niệm dịch vụ IPTV …………………………..………………. Một số ƣu điểm và nhƣợc điểm của dịch vụ IPTV ..

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