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Robert B. Ash

dblp:84/2916 · DBLP profile ↗
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5ranked-venue papers
3as first author
0since 2021 · last 1965
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 4 · 3 first-authorSystems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
4 papers
Coding theory · 60% Information theory · 40%
Computer networks
2 papers
Physical-layer communications · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Hardware reliability and fault tolerance · 100%

Topics — the 9 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › information theory › capacity analysis
channel capacity
0.021964
Further Discussion of a Time-Continuous Gaussian Channel · Inf. Control. 1964
Capacity and Error Bounds for a Time-Continuous Gaussian Channel · Inf. Control. 1963
Information theory › channel capacity
gaussian channel
0.021964
Further Discussion of a Time-Continuous Gaussian Channel · Inf. Control. 1964
Capacity and Error Bounds for a Time-Continuous Gaussian Channel · Inf. Control. 1963
Coding theory › error-correcting codes
burst error correction
0.011963
Analysis of recurrent codes · IEEE Trans. Inf. Theory 1963
Information theory
channel capacity
0.011965
A simple example of a channel for which the strong converse fails (Corresp.) · IEEE Trans. Inf. Theory 1965
Coding theory › error-correcting codes
convolutional codes
0.011963
Analysis of recurrent codes · IEEE Trans. Inf. Theory 1963
Coding theory
error-correcting codes
0.011963
Analysis of recurrent codes · IEEE Trans. Inf. Theory 1963
Coding theory › error-correcting codes › convolutional codes
recurrent codes
0.011963
Analysis of recurrent codes · IEEE Trans. Inf. Theory 1963
Coding theory › channel coding
strong converse
0.011965
A simple example of a channel for which the strong converse fails (Corresp.) · IEEE Trans. Inf. Theory 1965
Hardware reliability and fault tolerance
reliability modeling
0.011959
Increasing Reliability by the Use of Redundant Machines · IRE Trans. Electron. Comput. 1959

Methods — techniques the papers use, named apart from their topics

mathematical analysis · 0.0markov modeling · 0.0lower bound derivation · 0.0cost analysis · 0.0
YearPublicationVenuePosition
1965 A simple example of a channel for which the strong converse fails (Corresp.)
Robert B. Ash
IEEE Trans. Inf. Theory1
1964 Further Discussion of a Time-Continuous Gaussian Channel
Robert B. Ash
Inf. Control.1
1963 Capacity and Error Bounds for a Time-Continuous Gaussian Channel
Robert B. Ash
Inf. Control.1
1963 Analysis of recurrent codes
abstract
A definition of a recurrent code is given in a framework which renders it amenable to mathematical analysis. Recurrent codes for both independent and burst errors are considered, and a necessary and sufficient condition for either type of error correction is established. For burst-error-correcting codes, the problem treated is (for a fixed burst length and redundancy) the minimization of the error-free distance ("guard space") required between bursts. A lower bound is obtained on the guard space, and in certain cases, codes which realize this bound are given. A general code which is close to the lower bound in many cases is also given. For independent errors, a code which will correct any error, provided that no consecutive "n" positions have more than "e" digits in error, is discussed. Fore = 1, a necessary and sufficient condition onnis derived; fore > 1, a lower bound onnis obtained, and for the case of redundancy1/2, an upper bound onnis also derived.
Aaron D. Wyner, Robert B. Ash
IEEE Trans. Inf. Theory2
1959 Increasing Reliability by the Use of Redundant Machines
abstract
The improvement of reliability and availability through redundancy of entire machines rather than of components is investigated. An attempt is made to break down the cost of operating a digital computer, and to determine the relationship between cost and system failure. Three specific cases are discussed. Case 1: Where n machines are operated independently, processing the same input data. The output is taken from a single one of them; if this machine fails, the output is promptly switched to a machine which is operating properly. As soon as repairs can be completed, the machine which had failed is returned to operation. System failure occurs only when all n machines are in the failed condition at the same time. A penalty cost is assessed for system failure, this cost being proportional to the system down-time. Case 2: Where n machines are operated as in Case 1, except that any machines which fail are not returned to operation until the beginning of the next operating period. Penalty cost for system failure is assessed in the same way as in Case 1. Case 3: Where n machines are operated as in Case 2, but where the penalty cost for system failure is a fixed amount and is independent of the resulting down-time.
Donald E. Rosenheim, Robert B. Ash
IRE Trans. Electron. Comput.2