This course will provides you the fundamentals of Digital Signal Processing from the ground up. Starting from the basic definition of a discrete-time signal, you will go 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.
These lectures note are part of the BOOC series (Book and Open Online Courses), a collection of reading material supporting the MOOCs (Massive Open Online Courses) provided by the Ecole Polytechnique Fédérale de Lausanne. These documents ideally complement the course, as they help revising the MOOC and obtain the certificate.
- Module 1: Introduction to Digital Signal Processing – Discrete Time Signals – How Does Your PC Play Discrete-Time Sound? – The Karplus-Strong Algorithm – Complex Exponentials
- Module 2: Signal Processing and Vector Spaces – Vector Space – Signal Space – Bases – Subspace-Based Approximation
- Module 3: The Frequency Domain – The DFT as a Change of Basis – The Definition of DFT – Examples of DFT Calculation – Interpreting a DFT Plot – DFT Analysis – DFT Example – Analysis of Musical Instruments – DFT Synthesis – DFT Example: Tide Prediction in Venice – DFT Example: MP3 Compression – The Short-Time Fourier Transform – The Spectrogram – Time-Frequency Tiling – Discrete Fourier Series – Karplus-Strong Revisited and DFS – Karplus-Strong Revisited and DTFT – Existence and Properties of the DTFT – The DTFT as a Change of Basis – Sinusoidal Modulation – Tuning a Guitar
- Module 4: Linear Time-Invariant Filters – Convolution – The Moving Average Filter – The Leaky Integrator – Filter Classification in the Time Domain – Filter Stability – The Convolution Theorem – Examples of Frequency Response – Filter Classification in the Frequency Domain – The Ideal Lowpass Filter – Ideal Filters Derived from the Ideal Lowpass Filter – Demodulation Revisited – Impulse Truncation and Gibbs Phenomenon – Window Method – Frequency Sampling – The z-Transform – Region of Convergence and Stability – Intuitive IIR Design – Filter Specification – IIR Design – FIR design
- Module 5: The Continuous-Time Paradigm – Continuous-Time Signal Processing – Polynomial Interpolation – Local Interpolation – The Spectrum of Interpolated Signals – The Space of Band-Limited Functions – The Sampling Theorem – Raw Sampling – Sinusoidal Aliasing – Aliasing for Arbitrary Spectra – Sampling Strategies – Stochastic Signal Processing – Quantization
- Module 6: The Success Factors for Digital Communication – Constraints of the Analog Channel – The Design Problem – Upsampling – Fitting the Transmitter Spectrum – Noise and Probability of Error – PAM and QAM – Modulation and Demodulation – Design Example – Receiver Design – Delay Compensation – Adaptive Equalization – ADSL Design – Discrete Multitone Modulation
Pages count eBook [PDF]: 91
EAN13 eBook [PDF]: 9782889144259
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