Design of one-pass training algorithms for variant morphological operations

Jenlong Moh; Frank Y. Shih

doi:10.1016/0020-0255(96)88797-4

Design of one-pass training algorithms for variant morphological operations

Jenlong Moh, Frank Y. Shih

Computer Science

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

1 Scopus citations

Abstract

In this paper, the design of one-pass training algorithms for variant morphological operations is presented. The algorithms intend to achieve a fast-learning goal in which the morphological neurons can learn a training pattern and memorize it in exactly one training iteration. Furthermore, only simple computations are used to allow easy implementation in hardware. The proofs of the training algorithms and the program-simulated experimental results are provided.

Original language	English (US)
Pages (from-to)	303-314
Number of pages	12
Journal	Information sciences
Volume	94
Issue number	1-4
DOIs	https://doi.org/10.1016/0020-0255(96)88797-4
State	Published - Oct 1996

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Software
Control and Systems Engineering
Computer Science Applications
Information Systems and Management
Artificial Intelligence

Access to Document

10.1016/0020-0255(96)88797-4

Cite this

@article{2f83ec8c7873483d841848ca0f52ad9d,

title = "Design of one-pass training algorithms for variant morphological operations",

abstract = "In this paper, the design of one-pass training algorithms for variant morphological operations is presented. The algorithms intend to achieve a fast-learning goal in which the morphological neurons can learn a training pattern and memorize it in exactly one training iteration. Furthermore, only simple computations are used to allow easy implementation in hardware. The proofs of the training algorithms and the program-simulated experimental results are provided.",

author = "Jenlong Moh and Shih, {Frank Y.}",

year = "1996",

month = oct,

doi = "10.1016/0020-0255(96)88797-4",

language = "English (US)",

volume = "94",

pages = "303--314",

journal = "Information sciences",

issn = "0020-0255",

publisher = "Elsevier Inc.",

number = "1-4",

}

TY - JOUR

T1 - Design of one-pass training algorithms for variant morphological operations

AU - Moh, Jenlong

AU - Shih, Frank Y.

PY - 1996/10

Y1 - 1996/10

N2 - In this paper, the design of one-pass training algorithms for variant morphological operations is presented. The algorithms intend to achieve a fast-learning goal in which the morphological neurons can learn a training pattern and memorize it in exactly one training iteration. Furthermore, only simple computations are used to allow easy implementation in hardware. The proofs of the training algorithms and the program-simulated experimental results are provided.

AB - In this paper, the design of one-pass training algorithms for variant morphological operations is presented. The algorithms intend to achieve a fast-learning goal in which the morphological neurons can learn a training pattern and memorize it in exactly one training iteration. Furthermore, only simple computations are used to allow easy implementation in hardware. The proofs of the training algorithms and the program-simulated experimental results are provided.

UR - http://www.scopus.com/inward/record.url?scp=0030269859&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030269859&partnerID=8YFLogxK

U2 - 10.1016/0020-0255(96)88797-4

DO - 10.1016/0020-0255(96)88797-4

M3 - Article

AN - SCOPUS:0030269859

SN - 0020-0255

VL - 94

SP - 303

EP - 314

JO - Information sciences

JF - Information sciences

IS - 1-4

ER -

Design of one-pass training algorithms for variant morphological operations

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this