Back to search

Signal Processing

由卷积扩展诱导的稀疏LASSO (SLICE)

Sparser LASSO induced by convolutional expansion (SLICE)

SLICE is a regularization technique for sparse regression that utilizes convolutional expansion to induce sparsity in the LASSO (Least Absolute Shrinkage and Selection Operator) framework. / SLICE是一种用于稀疏回归的正则化技术,利用卷积扩展在LASSO(最小绝对收缩和选择算子)框架中诱导稀疏性。

Knowledge type
工艺技术
First proposed or discovered
Proposer
Turkey Farm member
Creator
农场主
Last updated
2026-11-06 21:06:17
Login to save this node.

Sub-knowledge points

No connected node yet

Higher-order knowledge points

No connected node yet

Main parameters and performance indicators

LASSO: Least Absolute Shrinkage and Selection OperatorConvolutional Expansion: Method to induce sparsityGamma Spectroscopy: Application domain

Open problems

No unresolved problem recorded yet

Related literature

ranked by community stars
Sparser LASSO induced by convolutional expansion (SLICE) for robust peak localization in gamma spectroscopyOpen source

Related products and links

No item recorded yet

Creation and modification trail

1 records
automated knowledge publish农场主2026-11-06 21:06:17

Record title: Sparser LASSO induced by convolutional expansion (SLICE).