Spike encoders are reformulated as time-causal bandpass wavelets that preserve sparsity and locality while providing reconstruction error bounds comparable to continuous wavelet transforms on ECG and audio signals.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
SCOPE is a parameter-free splicing-based algorithm for sparsity-constrained optimization of strongly convex smooth objectives that achieves linear convergence and exact support recovery without relying on RIP-type conditions.
Introduces group sparsity constraint and soft energy lower bound in compressed sensing to reconstruct directional wave spectra from sparse multi-channel buoy data.
New inconsistent alternating projection scheme for basis pursuit with linear convergence proofs and competitive benchmarks.
citing papers explorer
-
Encoding and Decoding Temporal Signals with Spiking Bandpass Wavelets
Spike encoders are reformulated as time-causal bandpass wavelets that preserve sparsity and locality while providing reconstruction error bounds comparable to continuous wavelet transforms on ECG and audio signals.
-
Sparsity-Constraint Optimization via Splicing Iteration
SCOPE is a parameter-free splicing-based algorithm for sparsity-constrained optimization of strongly convex smooth objectives that achieves linear convergence and exact support recovery without relying on RIP-type conditions.
-
Recovery of directional wave spectrum from sparse data with compressed sensing
Introduces group sparsity constraint and soft energy lower bound in compressed sensing to reconstruct directional wave spectra from sparse multi-channel buoy data.
-
Basis pursuit by inconsistent alternating projections
New inconsistent alternating projection scheme for basis pursuit with linear convergence proofs and competitive benchmarks.