Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robo...
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In this paper, the application of a real-time fuzzy controller is presented in order to improve the power system stability. The above is done with the means of the fuzzy membership functions whose values are computed ...
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In this paper, the application of a real-time fuzzy controller is presented in order to improve the power system stability. The above is done with the means of the fuzzy membership functions whose values are computed depending on the measured generator frequency and voltage. The controller was tested in real time for different loads on the generator. For comparison a proportional crisp controller was also design and tested under the same circumstances.
A modular neural network architecture is proposed to classify binary and continuous patterns. This system consists of a supervised feedforward backpropagation network and an unsupervised self-organization map network....
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A modular neural network architecture is proposed to classify binary and continuous patterns. This system consists of a supervised feedforward backpropagation network and an unsupervised self-organization map network. The supervised feedforward (basic) network is trained until a saturation error level occurs. Simultaneously, the unsupervised self-organization map (control) network fluids the mapping features for the given input/output patterns. The resultant features are used by Gaussian and linear functions to adjust the hidden and the output weights of the basic network and to classify the given patterns.< >
In this paper fuzzy control and decision making are used to simulate the control of traffic flow at an intersection. Fuzzy logic can be used as an alternative method for control of traffic environments. A traffic envi...
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In this paper fuzzy control and decision making are used to simulate the control of traffic flow at an intersection. Fuzzy logic can be used as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller a computer simulation is constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. The fuzzy logic controller proved to be a better method of control than conventional control methods, especially in the case of highly uneven traffic flow between different directions
Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robo...
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Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robot among obstacles in structured and/or unstructured environments with collision-free motion as the proirity. A fuzzy logic based intelligent control strategy has been developed here to computationally implement the approximate reasoning necessary for handling the uncertainty inherent in the collision avoidance problem.< >
This paper presents a neural network approach to differential pulse code modulation (DPCM) design for the encoding of images. Instead of traditional algorithms for the computation of the relevant coefficients, such as...
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This paper presents a neural network approach to differential pulse code modulation (DPCM) design for the encoding of images. Instead of traditional algorithms for the computation of the relevant coefficients, such as the autocovariance and autocorrelation methods, the predictor is designed by supervised training of a neural network on examples, i.e. on a typical sequence of pixel values. This allows the use of nonlinear as well as linear correlations. Efficient and fast neural net architectures, for nonlinear one-dimensional DPCM (NNDPCM) as well as two-dimensional adaptive DPCM (NNADPCM), have been designed and applied to still image coding. computer simulation experiments have shown that the resulting encoders work very well. At a transmission rate of 1 bit/pixel, the 1-D NNDPCM offers an advantage of about 4dB in peak signal-to-noise ratio over the standard linear DPCM system. At a bit rate of 0.525 bit/pixel, the 2-D NNADPCM achieves 29.5 dB for the 512 x 512 Lena image, while there is little visible distortion in the reconstructed image. This performance is comparable to that of the best schemes known to date, whether DPCM based or not, while maintaining a lower encoding complexity. Furthermore, this establishes that there is substantial amount of nonlinear content available for 1-D and 2-D prediction in DPCM image coding.
The performance of the CEBus, a proposed computer network standard for the intelligent home, implemented with Power Line (PL) and Twisted Pair (TP) media, interconnected through a router, has been investigated. The de...
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The performance of the CEBus, a proposed computer network standard for the intelligent home, implemented with Power Line (PL) and Twisted Pair (TP) media, interconnected through a router, has been investigated. The delay and throughput characteristics of each of the three priority class of messages, i.e., DEFERRED, STANDARD and HIGH, have been measured. Overall, the PL - Router - TP network system has behaved well and as expected, however care must be taken to restrict traffic from the high (TP) to the low (PL) capacity medium to reasonable levels from the point of view of the low capacity medium.
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