Audio coding format

Applied sciences
Information engineering
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Data compression

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Related lectures (32)

Page 3 of 4

Data Compression and Shannon's Theorem Summary

Summarizes Shannon's theorem, emphasizing the importance of entropy in data compression.

Data Compression and Entropy: Basics and Introduction

Introduces data compression, entropy, and the importance of reducing redundancy in data.

Data Compression and Shannon Fano Coding

Explores practical data compression using Shannon Fano coding and the engineering challenges of compressing diverse data types.

Feasible LID Systems: Transfer Functions and Stability

Explores feasible LID systems, rational transfer functions, stability, causality, and implementation parameters in computing.

Contrastive losses: Word2Vec and Skip-gram

Covers contrastive losses in Word2Vec and Skip-gram models, negative sampling, Noise Contrastive Estimation, and InfoNCE/CPC.

Special Cases: Perfect Conductors and Lossy Media

Discusses perfect conductors and lossy media, exploring total reflection and wave attenuation.

Data Compression and Shannon's Theorem: Shannon-Fano Coding

Explores Shannon-Fano coding for efficient data compression and its comparison to Huffman coding.

Configuring Audio Visual Systems: User Interfaces and Settings

Covers the configuration of audio-visual systems using IPCP Pro and TLP Pro devices.

Data Compression: Entropy Definition

Explores data compression through entropy definition, types, and practical examples, illustrating its role in efficient information storage and transmission.

Compression: introduction

Introduces data compression, exploring how redundancy in data can be reduced to achieve smaller file sizes without losing information.