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TIME: TASKS

by unknown authors , 2001
"... (T) = TIME CRITICAL ..."
Abstract - Add to MetaCart
(T) = TIME CRITICAL

Finding structure in time

by Jeffrey L. Elman - COGNITIVE SCIENCE , 1990
"... Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a pro ..."
Abstract - Cited by 2071 (23 self) - Add to MetaCart
Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a

Real-Time Dynamic Voltage Scaling for Low-Power Embedded Operating Systems

by Padmanabhan Pillai, Kang G. Shin , 2001
"... In recent years, there has been a rapid and wide spread of nontraditional computing platforms, especially mobile and portable computing devices. As applications become increasingly sophisticated and processing power increases, the most serious limitation on these devices is the available battery lif ..."
Abstract - Cited by 501 (4 self) - Add to MetaCart
importance, is largely overlooked/under-developed. To provide real-time guarantees, DVS must consider deadlines and periodicity of real-time tasks, requiring integration with the real-time scheduler. In this paper, we present a class of novel algorithms called real-time DVS (RT-DVS) that modify the OS

Timing-Sync Protocol for Sensor Networks

by Saurabh Ganeriwal, Ram Kumar, Mani B. Srivastava - The First ACM Conference on Embedded Networked Sensor System (SenSys , 2003
"... Wireless ad-hoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages that are ..."
Abstract - Cited by 515 (8 self) - Add to MetaCart
Wireless ad-hoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages

Real-Time Obstacle Avoidance for Manipulators and Mobile Robots

by Oussama Khatib - INT. JOUR OF ROBOTIC RESEARCH , 1986
"... This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi-tionally considered a high level planning problem, can be effectively distributed between different levels of control, al- ..."
Abstract - Cited by 1345 (28 self) - Add to MetaCart
This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi-tionally considered a high level planning problem, can be effectively distributed between different levels of control, al

Dual-task interference in simple tasks: Data and theory

by Harold Pashler - Psychological Bulletin , 1994
"... People often have trouble performing 2 relatively simple tasks concurrently. The causes of this interference and its implications for the nature of attentional limitations have been controversial for 40 years, but recent experimental findings are beginning to provide some answers. Studies of the psy ..."
Abstract - Cited by 434 (12 self) - Add to MetaCart
of the psychological refractory period effect indicate a stubborn bottleneck encompassing the process of choosing actions and probably memory retrieval generally, together with certain other cognitive operations. Other limitations associated with task preparation, sensory-perceptual processes, and timing can generate

A Multiframe Model for Real-Time Tasks

by Aloysius K. Mok, Deji Chen - IEEE Transactions on Software Engineering , 1996
"... The well-known periodic task model of Liu and Layland [1] assumes a worst-case execution time bound for every task and may be too pessimistic if the worst-case execution time of a task is much longer than the average. In this paper, we give a multiframe real-time task model which allows the executio ..."
Abstract - Cited by 149 (7 self) - Add to MetaCart
The well-known periodic task model of Liu and Layland [1] assumes a worst-case execution time bound for every task and may be too pessimistic if the worst-case execution time of a task is much longer than the average. In this paper, we give a multiframe real-time task model which allows

On the time course of perceptual choice: the leaky competing accumulator model

by Marius Usher, James L. McClelland - PSYCHOLOGICAL REVIEW , 2001
"... The time course of perceptual choice is discussed in a model based on gradual and stochastic accumulation of information in non-linear decision units with leakage (or decay of activation) and competition through lateral inhibition. In special cases, the model becomes equivalent to a classical diffus ..."
Abstract - Cited by 480 (19 self) - Add to MetaCart
diffusion process, but leakage and mutual inhibition work together to address several challenges to existing diffusion, random-walk, and accumulator models. The model provides a good account of data from choice tasks using both time-controlled (e.g., deadline or response signal) and standard reaction time

A Learning Algorithm for Continually Running Fully Recurrent Neural Networks

by Ronald J. Williams, David Zipser , 1989
"... The exact form of a gradient-following learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a precis ..."
Abstract - Cited by 534 (4 self) - Add to MetaCart
The exact form of a gradient-following learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a

Making Large-Scale Support Vector Machine Learning Practical

by Thorsten Joachims , 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract - Cited by 628 (1 self) - Add to MetaCart
learning tasks with many training examples, off-the-shelf optimization techniques for general quadratic programs quickly become intractable in their memory and time requirements. SVM light1 is an implementation of an SVM learner which addresses the problem of large tasks. This chapter presents
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