Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
129 tokens/sec
GPT-4o
28 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Deterministic Construction of RIP Matrices in Compressed Sensing from Constant Weight Codes (1506.02568v2)

Published 8 Jun 2015 in cs.IT and math.IT

Abstract: The expicit restricted isometry property (RIP) measurement matrices are needed in practical application of compressed sensing in signal processing. RIP matrices from Reed-Solomon codes, BCH codes, orthogonal codes, expander graphs have been proposed and analysised. On the other hand binary constant weight codes have been studied for many years and many optimal or near-optimal small weight and ditance constant weight codes have been determined. In this paper we propose a new deterministic construction of RIP measurement matrices in compressed sensing from binary and ternary contant weight codes. The sparse orders and the number of budged rows in the new constant-weight-code-based RIP matrices can be arbitrary. These contant-weight-code based RIP matrices have better parameters compared with the DeVore RIP matrices when the sizes are small.

Citations (3)

Summary

We haven't generated a summary for this paper yet.