Multirate Signal Processing with Python Examples - Full Course - Ilmenau University of Technology скачать в хорошем качестве

Multirate Signal Processing with Python Examples - Full Course - Ilmenau University of Technology

Department of Electrical Engineering and Information Technology Module leader: Prof. Dr. Gerald Schuller Credit Points: 4 Obligation: obligatory At the end of the course the student is able to understand, design, and apply multirate signal processing systems, as filter banks, transforms, or Wavelets, to multimedia systems. 00:00:00 Introduction What is Multirate Signal Processing? Discrete Time Signal Example Python Live Plot of a Microphone Signal Javascript Live Plot of a Microphone Signal Nyquist Theorem Simple Sample Rate Conversion Example Basic Building Blocks of MSP Example: Basic Building Blocks Critical Sampling Analysis Filter Bank Analysis Filter Bank Explanation Synthesis Filter Bank 00:24:00 Multiresolution Uniform Filter Banks Live Spectrogram Example Non-Uniform Filter Banks Notation DTFT - Discrete-Time Fourier Transform DFT - Discrete Fourier Transform DCT - Discrete Cosine Transform z-Transform z-Transform Examples STFT - Short-Time Fourier Transform 01:06:00 Frequency Response Frequency Response using Noise Black Box System / Noise Gaussian Noise Output of Black Box 01 Transfer Function Black Box 01 Impulse Response Black Box 01 Butterworth Filter Frequency Response using Sweeping Sinusoid Transfer Function using Sweeping Sinusoid Convolution as Matrix Multiplication z-Transform Frequency Response Python FreqZ Function Frequency Response Other Plots dB Revision - The decibel Cascaded Filters 01:50:00 Filters Ideal Low Pass Filter Delay (Shift) Operator Ideal Low Pass Filter Impulse Response 02:01:00 Filters and Windows Finite Impulse Response (FIR) Low Pass Filter Parseval Theorem Rectangular Window Frequency Response Approximation of an Ideal Low Pass Filter 02:32:00 Window Functions Window Design using Optimization Error Function for Optimization Raised Cosine Window Kaiser Window Window Function used in Vorbis I 02:47:00 Filter Design with the Window Method The Window Method Kaiser Window Example Kaiser Window Example: Python Kaiser Window Longer Example: Python High Pass and Band Pass Ideal Filter Design High Pass and Band Pass with Modulation HP and BP with Modulation: Python Example HP and BP with Modulation: Python Example II 03:08:00 Sampling Python Example - Downsampling & Upsampling 03:14:00 Effects in the z-Domain The z-Transform Modulation and Time Reversal 03:23:30 Non-Ideal Filters Non-Ideal Filters Filter Banks Aliasing Cancellation Analysis Filter Bank Live Spectrogram in Python Fast Implementation 03:41:00 Transforms as Filter Banks Equivalent Analysis Filters of a Discrete Fourier Transform (DFT) Equivalent Synthesis Filter Bank Python Example Example Transform as Filter Bank 03:57:00 Discrete Cosine Transform and Polyphase Representation DCT Type 4 Polyphase Introduction Polyphase Python Example Polyphase Faster Implementation Polyphase Application Example 04:20:00 Polyphase Representation Filter Bank of N Filters Synthesis Filter Bank Perfect Reconstruction Auxiliary Python Functions 04:32:00 Modified Discrete Cosine Transform (MDCT) MDCT Python Example: MDCT Filters Analysis and Synthesis Polyphase Matrices Symmetries of a Cosine Modulation Function Sparse Matrices and the MDCT Factorization: Python Example The Delay Matrix Python Examples The Python Folding Matrix Function The Factorization Perfect Reconstruction Nested 2x2 Sub-Matrices Orthogonality and Para-Unitarity Fa Matrix MDCT Python Implementation, Analysis MDCT Synthesis Filter Bank 05:28:00 Low Delay Filter Banks (LDFB) Low Delay Filter Banks Folding Matrix Fa Zero-Delay Matrix Zero-Delay Matrix and its Inverse Sympy Implementation Python Sympy Example: Folding Matrix and Zero-Delay Matrix Drawbacks of Zero-Delay Matrices Python Fast Implementation Example 05:52:00 Optimization of Filter Banks Goal Problem to Solve Optimization Approach Newton's Method Gradient Hesse Matrix Gradient Descent Python Example for the Optimization of an MDCT Filter Bank 06:21:00 Artificial Neural Networks Neural Networks as Cascaded Filter Banks Deep Neural Networks Activation Function Diagram of a 3-layer Artificial Neural Network Gradient Descent Back Propagation Python Example: MNIST Digit Recognition Convolutional Neural Networks Python Keras CNN Example Python PyTorch Example Convolutional Implementation Using a Dense Net Real-Time Online Implementation of Convolutional Neural Networks #python #signalprocessing #freecourse