Erratum: Deep neural networks with random Gaussian weights: A universal classification strategy? (IEEE Transactions on Signal Processing (2016) 64:13 (3444-3457) DOI: 10.1109/TSP.2016.2546221)

Raja Giryes; Guillermo Sapiro; Alex M. Bronstein

doi:10.1109/TSP.2019.2961228

Erratum: Deep neural networks with random Gaussian weights: A universal classification strategy? (IEEE Transactions on Signal Processing (2016) 64:13 (3444-3457) DOI: 10.1109/TSP.2016.2546221)

Raja Giryes
, Guillermo Sapiro
, Alex M. Bronstein

Research output: Contribution to journal › Comment/debate › peer-review

4 Scopus citations

Abstract

Following a comment correspondence paper, we agree that there is a mistake in one of the formulas in the paper "Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy? "We show that this error only impacts one claim in the original paper.

Original language	English (US)
Article number	8974655
Pages (from-to)	529-531
Number of pages	3
Journal	IEEE Transactions on Signal Processing
Volume	68
DOIs	https://doi.org/10.1109/TSP.2019.2961228
State	Published - 2020
Externally published	Yes

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering

Access to Document

10.1109/TSP.2019.2961228

Cite this

@article{7d77fb61d6cc4693b5c60669acbf0e63,

title = "Erratum: Deep neural networks with random Gaussian weights: A universal classification strategy? (IEEE Transactions on Signal Processing (2016) 64:13 (3444-3457) DOI: 10.1109/TSP.2016.2546221)",

abstract = "Following a comment correspondence paper, we agree that there is a mistake in one of the formulas in the paper {"}Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy? {"}We show that this error only impacts one claim in the original paper.",

author = "Raja Giryes and Guillermo Sapiro and Bronstein, \{Alex M.\}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.",

year = "2020",

doi = "10.1109/TSP.2019.2961228",

language = "English (US)",

volume = "68",

pages = "529--531",

journal = "IEEE Transactions on Signal Processing",

issn = "1053-587X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Erratum: Deep neural networks with random Gaussian weights: A universal classification strategy? (IEEE Transactions on Signal Processing (2016) 64:13 (3444-3457) DOI: 10.1109/TSP.2016.2546221). / Giryes, Raja; Sapiro, Guillermo; Bronstein, Alex M.
In: IEEE Transactions on Signal Processing, Vol. 68, 8974655, 2020, p. 529-531.

Research output: Contribution to journal › Comment/debate › peer-review

TY - JOUR

T1 - Erratum

T2 - Deep neural networks with random Gaussian weights: A universal classification strategy? (IEEE Transactions on Signal Processing (2016) 64:13 (3444-3457) DOI: 10.1109/TSP.2016.2546221)

AU - Giryes, Raja

AU - Sapiro, Guillermo

AU - Bronstein, Alex M.

PY - 2020

Y1 - 2020

N2 - Following a comment correspondence paper, we agree that there is a mistake in one of the formulas in the paper "Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy? "We show that this error only impacts one claim in the original paper.

AB - Following a comment correspondence paper, we agree that there is a mistake in one of the formulas in the paper "Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy? "We show that this error only impacts one claim in the original paper.

UR - https://www.scopus.com/pages/publications/85082654706

UR - https://www.scopus.com/pages/publications/85082654706#tab=citedBy

U2 - 10.1109/TSP.2019.2961228

DO - 10.1109/TSP.2019.2961228

M3 - Comment/debate

AN - SCOPUS:85082654706

SN - 1053-587X

VL - 68

SP - 529

EP - 531

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

M1 - 8974655

ER -

Erratum: Deep neural networks with random Gaussian weights: A universal classification strategy? (IEEE Transactions on Signal Processing (2016) 64:13 (3444-3457) DOI: 10.1109/TSP.2016.2546221)

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this