Lecture
Signal Processing: Basic Definitions and Signal Typology
Related lectures (33)
Sampling and Reconstruction
Covers the concepts of sampling and reconstruction in signal processing, emphasizing the importance of sampling frequency and reconstruction techniques.
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.
Optimization of Neuroprosthetic Systems
Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.
Noise: Signal Processing
Explores types of noise in signal processing and methods to mitigate interference.
Sampling and Reconstruction Theory
Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.
Signal Sampling: Sampling
Explains signal sampling, the need for discrete sampling, errors, quantization, and choosing the right sampling period.
Signals & Systems I: Introduction to Communication Systems
Covers the basics of signals and systems in communication, including modulation, medical imaging, Fourier analysis, and biological systems.
Neural Signals and Signal Processing
Explores neural signals, EMG control, muscle synergies, and HD-EMG for prosthetic devices.
Graphical Convolution
Covers the graphical convolution method for discrete-time signals and explains the continuous-time convolution with examples.
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.