Cellular Neural Networks Based Time-Series Approximation for Real Time Systems’ Modeling-and-Identification and Behavior Forecast in Transportation: Motivation, Problem Formulation, and Some Research Avenues

2012 ◽  
pp. 241-254 ◽  
Author(s):  
Jean Chamberlain Chedjou ◽  
Kyandoghere Kyamakya
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Real Time ◽  
Problem Formulation ◽  
Cellular Neural Networks ◽  
Systems Modeling ◽  
Real Time Systems ◽  
Series Approximation ◽  
And Behavior ◽  
Time Systems

Use of neural networks to recover from software faults in real-time systems

1994 ◽  
Author(s):  
Erwin L. Hunter ◽  
Abhijit S. Pandya ◽  
Neal Coulter
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Real Time Systems ◽  
Software Faults ◽  
Time Systems

Timing isolation and improved scheduling of deep neural networks for real‐time systems

2020 ◽  
Vol 50 (9) ◽  
pp. 1760-1777 ◽  
Author(s):  
Daniel Casini ◽  
Alessandro Biondi ◽  
Giorgio Buttazzo
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Deep Neural Networks ◽  
Real Time Systems ◽  
Time Systems

Requirements-based testing of real-time systems: Modeling for testability

Computer ◽  
1985 ◽  
Vol 18 (4) ◽  
pp. 71-80 ◽  
Author(s):  
Chandrasekharan ◽  
Dasarathy ◽  
Kishimoto
Keyword(s):  
Real Time ◽  
Systems Modeling ◽  
Real Time Systems ◽  
Time Systems

VLSI Implementation of Neural Classifiers

1990 ◽  
Vol 2 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Arun Rao ◽  
Mark R. Walker ◽  
Lawrence T. Clark ◽  
L. A. Akers ◽  
R. O. Grondin
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Associative Memory ◽  
Binary Classification ◽  
Real Time Systems ◽  
Classification Schemes ◽  
Pipelined Architecture ◽  
Hardware Implementations ◽  
Fixed Radius ◽  
Time Systems

The embedding of neural networks in real-time systems performing classification and clustering tasks requires that models be implemented in hardware. A flexible, pipelined associative memory capable of operating in real-time is proposed as a hardware substrate for the emulation of neural fixed-radius clustering and binary classification schemes. This paper points out several important considerations in the development of hardware implementations. As a specific example, it is shown how the ART1 paradigm can be functionally emulated by the limited resolution pipelined architecture, in the absence of full parallelism.

ADDING FORM TO REAL-TIME SYSTEM SPECIFICATION AND SIMULATION

1999 ◽  
Vol 09 (05) ◽  
pp. 643-661 ◽  
Author(s):  
JI Y. LEE ◽  
KYO C. KANG ◽  
GERARD J. KIM ◽  
HYE J. KIM
Keyword(s):  
Real Time ◽  
Critical Role ◽  
Real Time Systems ◽  
System Specification ◽  
Time System ◽  
Real Time System ◽  
Interactive Behavior ◽  
Behavior Function ◽  
And Behavior ◽  
Time Systems

Specification and validation of a real-time system are often based on making simplistic predictions and assumptions about relevant behavior of the external environment and the controlled device interacting with it. However, in many cases, real-time systems physically interact with other external objects in a complex manner in a dynamically changing world and thus, their form (e.g. physical properties such as shape, mass, material, and configuration) can play a critical role in producing a correct specification and obtaining realistic simulation output. We present ASADAL/PROTO, a specification and simulation tool for real-time systems, that takes form into account in addition to the function and behavior handled by ASADAL/SIM, its predecessor. Simulation of the control system specification runs in conjunction with the environmental simulation, and the resulting interactive behavior of the controlled system is observed visually for analysis. Our vision is to incrementally model, simulate and analyze all three views (behavior, function, and form) of real-time system specification for its increased level of confidence at early prototyping stage.

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