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Statistical Signal & Data Processing
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Related lectures (54)
Signals & Systems I: Cross-Correlation and Convolution
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Explores cross-correlation, signal detection, Hilbert spaces, orthogonal approximation, and image compression using DCT.
Clustering Methods
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Explores clustering methods for partitioning data into meaningful classes when labeling is unknown, covering K-means, dissimilarity measures, and hierarchical clustering.
Image Processing I: Correlation Measures and Matched Filtering
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Explores correlation measures, matched filtering, and feature extraction in image processing.
Noise Formalism in Photodetectors: Understanding Detection Limits
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Discusses the formalism of noise in photodetectors, focusing on detection limits and the relationship between input power and output current.
High-order Correlations in Massive Datasets
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Delves into high-order correlations in massive datasets and their importance.
Neural Recording Techniques and Systems
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Explores neural recording techniques, systems, amplifiers, and high-value resistor integration for low-power optimization.
Parameter estimation
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Covers the concept of parameter estimation using the least square method.
Multivariate Gaussian Laws
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Explores multivariate Gaussian laws, covering probabilities, correlations, and conditional distributions in bivariate cases.
Fourier Transform: Problem Solving
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Covers solutions to a sample midterm, focusing on Fourier transform problems and system interconnections.
Extensions to Exchangeability: Statistical Analysis of Network Data
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Covers extensions to exchangeability in network data analysis, including graphon frameworks and edge exchangeability.
Principles of Finance: Risk and Return
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Explores risk and return in finance, covering securities' performance, rates of return, variance, volatility, and portfolio diversification.
Stochastic Models for Communications
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Covers stochastic models for binary transmission in communications systems.
Data Visualization: Techniques, Tools & Concepts
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Covers data visualization techniques, tools, and concepts for effective data representation.
Wireless Receivers: Gaussian Noise and Error Probability Estimation
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Covers wireless receivers in the presence of Gaussian noise and error probability estimation.
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