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Statistical Signal Processing Tools
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Related lectures (32)
Fourier Transform: Concepts and Applications
Covers the Fourier transform, its properties, applications in signal processing, and differential equations, emphasizing the concept of derivatives becoming multiplications in the frequency domain.
Signal Analysis and Filter Design
Explores signal analysis, FFT, filters, and power spectral density in signal processing.
Signals, Instruments, and Systems: System Properties and Transforms
Introduces system properties, Laplace Transform, and analog filters for signal analysis.
Numerical Methods: Boundary Value Problems
Covers numerical methods for solving boundary value problems using Crank-Nicolson and FFT.
Discrete Fourier Transform: Frequency Periodicity and Reconstruction
Explores frequency periodicity in the discrete Fourier transform for signal reconstruction.
Statistical Signal Processing
Covers Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.
Time Series: Multi-Tapering and Parametric Estimation
Covers Multi-Tapering and Parametric Estimation in Time Series analysis, including spectral estimation and AR model fitting.
Spectral Estimation: Periodogram and Tapering
Explores spectral representations, ACVS estimation, and spectral estimation in time series analysis.
Numerical Methods for Boundary Value Problems
Covers numerical methods for solving boundary value problems using finite difference, FFT, and finite element methods.
Frequency Response of LTI Systems
Explores LTI systems, impulse response, convolution, system properties, and frequency response, including low-pass and band-pass filters.
Fast Fourier Transform (FFT): Lecture 4
Covers the Fast Fourier Transform (FFT) algorithm, interpolation, filters, image processing, and experimental techniques in TEM and STM.
Multivariate Time Series and Spectral Representation
Explores multivariate time series analysis, emphasizing spectral representation and estimation methods.
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