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Coursera - Digital Signal Processing

Автор: Bo0mB0om » 5 мая 2016
Coursera - Digital Signal Processing
Coursera - Digital Signal Processing
English | mp4 | H264 960x540 | AAC 2 ch | 1.59 GB
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Learn the fundamentals of digital signal processing theory and discover the myriad ways DSP makes everyday life more productive and fun.

The goal of the course is to develop a complete working set of digital signal processing notions from the ground up. DSP is arguably at the heart of the "digital revolution" that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of information availability.
In the class, starting from the basic definitions of a discrete-time signal, we will work our way through Fourier analysis, filter design, sampling, interpolation and quantization to build a DSP toolset complete enough to analyze a practical communication system in detail. Hands-on examples and demonstration will be routinely used to close the gap between theory and practice.
Course Syllabus
Broad outline of the topics covered in the class:
Introduction: What is signal processing, history of the topic, application examples.
Discrete-time (DT) signals: the discrete-time complex exponential, and a computer music synthesis example.
Euclid and Hilbert: Signal processing as geometry, vectors spaces, bases, approximations.
Fourier Analysis: The discrete Fourier transform (DFT) and series (DFS). The discrete-time Fourier transform (DTFT). Examples. The fast Fourier transform algorithm (FFT).
Linear Filters: Linear time-invariant systems, convolution, ideal and realizable filters. Filter design and implementation, examples.
Interpolation and Sampling: Continuous-time (CT) signals, interpolation, sampling. The sampling theorem as orthonormal basis expansion. Processing of CT signals in DT.
Stochastic Signal Processing and Quantization: Stochastic signals, quantization, analog-to-digital (ADC) and digital-to-analog (DAC) conversion.
Image Processing: Introduction to image processing and two-dimensional (2D) Fourier analysis. Filtering and compression. The JPEG compression standard.
Digital Communication Systems: Analog channels and bandwidth/power constraints. Modulation and demodulation. Transmitter and receiver design. ADSL.
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