Singular Value Decomposition

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Presentation transcript:

Singular Value Decomposition Speaker : 詹承洲 Advisor : Prof. Andy Wu Date : 2008/01/22

Outline Introduction to Singular Value Decomposition Problem Statement What You Will Learn Expected Results

Motivation

Singular Value Decomposition Noise is not noise only anymore Collect the desired signals respectively instead of eliminating them

SVD for MIMO Systems SVD Mess!

Applications OFDM MIMO systems IEEE 802.11n (Wi-Fi) Antenna arrays

Problem Statement Algorithm domain: Architecture domain : Too complex computations Theoretical convergence problem No uniform solution Architecture domain : Large hardware complexity High-speed issue High power consumption

What You Will Learn Matrix computations Various SVD processing algorithms Evaluation of the performance of SVD algorithms

Expected Results Paper survey and acquaintance with SVD process Simulation for SVD algorithms Propose or modify existing SVD algorithms

Background Needed Linear algebra C or Matlab programming Probability (Optional) DSP or Communication Systems (Optional) Enthusiasm