MOOC
Digital Signal Processing IV
Lectures in this MOOC (120)
What is digital signal processingMOOC: Digital Signal Processing I
Covers the concept of time, discrete time practicality, sampling theorem, digital storage, transmission of signals, and key ideas of digital signal processing.
Discrete-time signals: Fundamentals and ApplicationsMOOC: Digital Signal Processing I
Covers the fundamentals of discrete-time signals, including analysis, synthesis, synchronization, cooling laws, and signal operations.
How your PC plays discrete-time soundsMOOC: Digital Signal Processing I
Covers digital-to-analog conversion and the role of sound cards in creating audio signals.
The Karplus-Strong AlgorithmMOOC: Digital Signal Processing I
Introduces the Karplus-Strong algorithm for synthesizing plucked-string sounds using digital signal processing.
Complex exponentials: Oscillations and advantagesMOOC: Digital Signal Processing I
Explores the use of complex exponentials to simplify trigonometry and algebra in digital systems.
Signal Processing: Goethe's Temperature MeasurementMOOC: Digital Signal Processing I
Explores the analysis of daily temperature measurements using signal processing techniques, showcasing the computation of moving averages and revealing long-term trends.
Signal processing and vector spacesMOOC: Digital Signal Processing I
Emphasizes the significance of vector spaces in signal processing, offering a unified framework for various signal types and system design.
Vector Spaces: BasicsMOOC: Digital Signal Processing I
Covers the basics of vector spaces, including operational definitions, properties, examples in RN, inner products, norms, and distances.
Signal spaces: Inner product, infinite-length signals, and completenessMOOC: Digital Signal Processing I
Covers signal spaces, inner product, infinite-length signals, and completeness in vector spaces.
Bases: Linear Combinations and Function SpacesMOOC: Digital Signal Processing I
Explores bases in vector spaces, including linear combinations, orthogonal bases, and basis transformations using rotation matrices.