The problem of designing recurrent continuous-time and spiking neural networks is NP-Hard. A common practice is to utilize stochastic searches, such as evolutionary algorithms, to automatically construct acceptable ne...
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The problem of designing recurrent continuous-time and spiking neural networks is NP-Hard. A common practice is to utilize stochastic searches, such as evolutionary algorithms, to automatically construct acceptable networks. The outcome of the stochastic search is related to its ability to navigate the search space of neural networks and discover those of high quality. In this paper we investigate the search space associated with designing the above recurrent neural networks in order to differentiate which network should be easier to automatically design via a stochastic search. Our investigation utilizes two popular dynamic systems problems; (1) the Henon map and (2) the inverted pendulum as a benchmark.
Optimization of robot dynamics for a given human motion is an intuitive way to approach the problem of learning complex human behavior by imitation. In this paper, we propose a methodology based on a learning approach...
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Optimization of robot dynamics for a given human motion is an intuitive way to approach the problem of learning complex human behavior by imitation. In this paper, we propose a methodology based on a learning approach that performs optimization of humanoid dynamics in a low-dimensional subspace. We compactly represent the kinematic information of humanoid motion in a low dimensional subspace. Motor commands in the low dimensional subspace are mapped to the expected sensory feedback. We select optimal motor commands based on sensory-motor mapping that also satisfy our kinematic constraints. Finally, we obtain a set of novel postures that result in superior motion dynamics compared to the initial motion. We demonstrate results of the optimized motion on both a dynamics simulator and a real humanoid robot
Design of a hardware efficient multiplier-less architecture for the computation of multi-dimensional convolution is presented in this paper. The new architecture performs computations in the logarithmic domain by util...
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Actual observed scenes usually produce a wide dynamic range. Currently available visual systems use low dynamic range light detector that provide only 8 bits of brightness information at each pixel. This greatly limit...
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An effective and robust image enhancement algorithm is presented for improving the visual quality of digital images captured under extremely low or non-uniform lighting conditions. The proposed algorithm is composed o...
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Development of a visibility improvement system for helping drivers with poor vision during night and bad weather conditions is proposed in this paper. Video streams captured by a CCD camera and an infrared camera are ...
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A modified approach on Modular PCA for face recognition is presented in this paper. The proposed changes aim to improve the recognition rates for modular PCA for face images with large variation in light and facial ex...
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Actual observed scenes usually produce a wide dynamic range. Currently available visual systems use low dynamic range light detector that provide only 8 bits of brightness information at each pixel. This greatly limit...
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Actual observed scenes usually produce a wide dynamic range. Currently available visual systems use low dynamic range light detector that provide only 8 bits of brightness information at each pixel. This greatly limits what visual systems can do for surveillance applications such as face detection and face recognition. A color image enhancement procedure based on the concept of color characterization, enhancement, and color balancing is proposed in this paper. The enhancement technique directly operates on pixels using a hyperbolic tangent function to increase the dynamic range of the pixel. The global and local statistics of the image is used to control the curvature of the hyperbolic tangent function. The color characterization and color balancing processes are based on a new nonlinear line attractor network to create a color manifold to restore the relationship of red, green, and blue components of the pixels. The proposed enhancement approach greatly improves the dynamic range compression and color rendition of an image.
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