Weak continuity with structural constraints

N. D. Sidiropoulos; J. S. Baras; C. A. Berenstein

doi:10.1109/78.650273

Weak continuity with structural constraints

N. D. Sidiropoulos
, J. S. Baras
, C. A. Berenstein

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Nonlinear regression and nonlinear regularization are two powerful approaches to segmentation and nonlinear filtering. In this correspondence, we propose a hybrid approach that effectively combines the best of both worlds and can be efficiently implemented via the Viterbi algorithm.

Original language	English (US)
Pages (from-to)	3096-3104
Number of pages	9
Journal	IEEE Transactions on Signal Processing
Volume	45
Issue number	12
DOIs	https://doi.org/10.1109/78.650273
State	Published - Dec 1997

Publisher link

10.1109/78.650273

Find It

Find It at U of M Libraries

Cite this

@article{ca45f363c5424e63a63e67832dce13ab,

title = "Weak continuity with structural constraints",

abstract = "Nonlinear regression and nonlinear regularization are two powerful approaches to segmentation and nonlinear filtering. In this correspondence, we propose a hybrid approach that effectively combines the best of both worlds and can be efficiently implemented via the Viterbi algorithm.",

author = "Sidiropoulos, \{N. D.\} and Baras, \{J. S.\} and Berenstein, \{C. A.\}",

year = "1997",

month = dec,

doi = "10.1109/78.650273",

language = "English (US)",

volume = "45",

pages = "3096--3104",

journal = "IEEE Transactions on Signal Processing",

issn = "1053-587X",

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

number = "12",

}

TY - JOUR

T1 - Weak continuity with structural constraints

AU - Sidiropoulos, N. D.

AU - Baras, J. S.

AU - Berenstein, C. A.

PY - 1997/12

Y1 - 1997/12

N2 - Nonlinear regression and nonlinear regularization are two powerful approaches to segmentation and nonlinear filtering. In this correspondence, we propose a hybrid approach that effectively combines the best of both worlds and can be efficiently implemented via the Viterbi algorithm.

AB - Nonlinear regression and nonlinear regularization are two powerful approaches to segmentation and nonlinear filtering. In this correspondence, we propose a hybrid approach that effectively combines the best of both worlds and can be efficiently implemented via the Viterbi algorithm.

UR - https://www.scopus.com/pages/publications/0031344569

UR - https://www.scopus.com/pages/publications/0031344569#tab=citedBy

U2 - 10.1109/78.650273

DO - 10.1109/78.650273

M3 - Article

AN - SCOPUS:0031344569

SN - 1053-587X

VL - 45

SP - 3096

EP - 3104

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

IS - 12

ER -

Weak continuity with structural constraints

Abstract

Publisher link

Find It

Other files and links

Fingerprint

Cite this