Fourier series and transforms

Xem 1-20 trên 26 kết quả Fourier series and transforms
  • Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications.

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  • You will understand the physical meaning behind the mathematics of wireless signals and learn the intricacies and tradeoffs in signal selection and design.

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  • Digital Signal Processing (DSP) is formally defined as a digital operation performed on an input sequence of numbers (including feedback from the result of the digital operation). The sequence of numbers can represent anything from digitised human speech to stock price data, processed to detect hidden periodicities or pattern

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  • Lecture Signal processing: Fourier representation of signals include all of the following content: Sinusoidal signals and their properties, fourier representation of continuous – time signals, fourier representation of discrete – time signals, summary of fourier series and fourier transforms, properties of the discrete – time fourier transform.

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  • (BQ) Part 2 book "Advanced engineering mathematics" has contents: Fourier series, the fourier integral and transforms, special functions and eigenfunction expansions, the wave equation, the heat equation, the potential equation, complex integration, singularities and the residue theorem,...and other contents.

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  • This book focuses on the Fourier transform applications in the analysis of some types of materials. The field of Fourier transform has seen explosive growth during the past decades, as phenomenal advances both in research and application have been made. During the preparation of this book, we found that almost all the textbooks on materials analysis have a section devoted to the Fourier transform theory. Most of those describe some formulas and algorithms, but one can easily be lost in seemingly incomprehensible mathematics....

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  • This book focuses on the Fourier transform applications in the analysis of some types of materials. The field of Fourier transform has seen explosive growth during the past decades, as phenomenal advances both in research and application have been made. During the preparation of this book, we found that almost all the textbooks on materials analysis have a section devoted to the Fourier transform theory. Most of those describe some formulas and algorithms, but one can easily be lost in seemingly incomprehensible mathematics.

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  • (BQ) Part 1 book "Signals and systems using MATLAB" has contents: From the ground up, continuous time signals, continuous time systems, the laplace transform, frequency analysis - The fourier series, frequency analysis - The fourier transform, application to control and communications.

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  • In this chapter, Fourier analysis will be discussed. Topics covered are Fourier series expansion, Fourier transform, discrete Fourier transform, and fast Fourier transform. Some applications of Fourier analysis, using MATLAB, will also be discussed.

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  • Fourier methods are commonly used for signal analysis and system design in modern telecommunications, radar, and image processing systems.

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  • Frequency analysis of any given signal involves the transformation of a time-domain signal into its frequency components. The need for describing a signal in the frequency domain exists because signal processing is generally accomplished using systems that are described in terms of frequency response. Converting the time-domain signals and systems into the frequency domain is extremely helpful in understanding the characteristics of both signals and systems. In Section 4.1, the Fourier series and Fourier transform will be introduced....

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  • In this chapter, Fourier analysis will be discussed. Topics covered are Fourier series expansion, Fourier transform, discrete Fourier transform, and fast Fourier transform. Some applications of Fourier analysis, using MATLAB, will also be discussed. 8.1 If a function FOURIER SERIES g (t ) is periodic with period Tp , i.e., (8.1) g (t ) = g (t ± Tp ) and in any finite interval g ( t ) has at most a finite number of discontinuities and a finite number of maxima and minima (Dirichlets conditions), and in addition, Tp ∫ g(t )dt ...

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  • Finite Impulse Response Filters • • • Introduction to the z-transform Design and implementation of finite impulse response (FIR) filters Programming examples using C and TMS320C6x code The z-transform is introduced in conjunction with discrete-time signals. Mapping from the s-plane, associated with the Laplace transform, to the z-plane, associated with the z-transform, is illustrated. FIR filters are designed with the Fourier series method and implemented by programming a discrete convolution equation.

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  • In this chapter, Fourier analysis will be discussed. Topics covered are Fourier series expansion, Fourier transform, discrete Fourier transform, and fast Fourier transform.

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  • POWER SPECTRUM AND CORRELATION Power Spectrum and Correlation Fourier Series: Representation of Periodic Signals Fourier Transform: Representation of Aperiodic Signals Non-Parametric Power Spectral Estimation Model-Based Power Spectral Estimation High Resolution Spectral Estimation Based on Subspace Eigen-Analysis Summary T he power spectrum reveals the existence, or the absence, of repetitive patterns and correlation structures in a signal process.

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  • Frequency Analysis Frequency analysis of any given signal involves the transformation of a time-domain signal into its frequency components. The need for describing a signal in the frequency domain exists because signal processing is generally accomplished using systems that are described in terms of frequency response. Converting the time-domain signals and systems into the frequency domain is extremely helpful in understanding the characteristics of both signals and systems. In Section 4.1, the Fourier series and Fourier transform will be introduced.

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  • Discrete Wavelet Transform is a wavelet (DWT) transform that is widely used in numerical and functional analysis. Its key advantage over more traditional transforms, such as the Fourier transform, lies in its ability to offer temporal resolution, i.e. it captures both frequency and location (or time) information.

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  • (BQ) Part 2 book "Wavelets and subband coding" has contents: Series expansions using wavelets and modulated bases; continuous wavelet and short time fourier transforms and frames; algorithms and complexity, signal compression and subband coding.

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  • (BQ) Part 1 book "Advanced engineering mathematics" has contents: First-Order ODEs; second-Order linear ODEs; higher order linear ODEs; systems of ODEs, phase plane, qualitative methods; laplace transforms; vector differential calculus - Grad, Div, Curl; partial differential equations (PDEs), fourier series, integrals, and transforms,...and other contents.

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  • (BQ) Part 1 book "Advanced engineering mathematics" has contents: First-Order ODEs, second-Order linear ODEs; higher order linear ODEs; systems of ODEs, phase plane, qualitative methods; laplace transforms; vector differential calculus - Grad, Div, Curl; partial differential equations (PDEs), fourier series, integrals, and transforms,...and other contents.

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