Digital Signal Processing 2: Filtering

This course is part of Digital Signal Processing Specialization

Instructors: Paolo Prandoni +1 more

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What you'll learn

  •   Digital filters, how they work
  •   Digital filter design
  •   Adaptive signal processing
  • Skills you'll gain

  •   Mathematical Modeling
  •   Engineering Calculations
  •   Numerical Analysis
  •   Linear Algebra
  •   Digital Communications
  •   Engineering Analysis
  •   Electronic Systems
  •   Computer Engineering
  •   Data Mapping
  •   Electrical Engineering
  •   Applied Mathematics
  •   Algorithms
  •   Real Time Data
  •   Electrical and Computer Engineering
  •   Telecommunications
  • There are 3 modules in this course

    The goal, for students of this course, will be to learn the fundamentals of Digital Signal Processing from the ground up. Starting from the basic definition 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. To make the best of this class, it is recommended that you are proficient in basic calculus and linear algebra; several programming examples will be provided in the form of Python notebooks but you can use your favorite programming language to test the algorithms described in the course.

    Module 2.2: Filter Design

    Module 2.3: Stochastic and Adaptive Signal Processing

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