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Poles, Zeros, and Stability: The Z-Transform in Action

The Z-transform is a powerful mathematical tool that extends the Fourier Transform to analyze discrete-time signals and systems. This article covers its fundamental concepts, including stability analysis, poles and zeros, and its role in solving difference equations.

Matrix Similarity and Basis Transformations

Discover how linear transformations are represented in different bases and why similar matrices preserve essential properties. Understand the mathematics behind change-of-basis operations.

Regularization: a method to avoid overfitting

Explains the principles and characteristics of L1 and L2 regularization, their connection to Maximum a Posteriori (MAP) estimation, and how to apply regularization to prevent overfitting in deep learning models.

Understanding the T-Test: A simple guide to statistical hypothesis testing

A statistical method used to evaluate whether differences between two sample means are significant or due to chance.

Cross-Entropy and KL Divergence: From Probability Distribution

A detailed exploration of Cross-Entropy and KL Divergence, deriving their formulas step-by-step from the principles of probability and information theory.

Denoising Diffusion Probabilistic Models (NeurIPS 2020)

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Poles, Zeros, and Stability: The Z-Transform in Action

The Z-transform is a powerful mathematical tool that extends the Fourier Transform to analyze discrete-time signals and systems. This article covers its fundamental concepts, including stability analysis, poles and zeros, and its role in solving difference equations.

Discrete Fourier Transform and Fast Fourier Transform

This post introduces the Discrete Fourier Transform (DFT) for frequency analysis and the Fast Fourier Transform (FFT), which optimizes computation using a divide-and-conquer approach.

From Analog to Digital: Sampling, Conversion, and Signal Reconstruction

This article explores the process of converting continuous analog signals into digital form, detailing each step—from pre-processing and A/D conversion to D/A reconstruction using methods like ideal, zero-order, and first-order holds. It also discusses key challenges such as aliasing and practical limitations in achieving perfect signal recovery.

Understanding LTI Systems: Impulse Response, Convolution, and Difference Equations

This article introduces the key concepts of LTI systems using impulse response, convolution, and difference equations. It explains how these concepts reveal the system's behavior and how to mathematically solve for its response.

Discrete signal and system: Concept of periodicity and LTI System

This article explores the basics of discrete-time signals, including periodic signals and key types like impulse, step, and exponential signals. It also explains LTI systems and how to analyze their stability.