Parallel Processing Capability Versus Efficiency of Representation in Neural Networks
نویسندگان
چکیده
Sebastian Musslick1 ([email protected]), Biswadip Dey2 ([email protected]) Kayhan Özcimder2 ([email protected]), Md. Mostofa Ali Patwary3 ([email protected]), Theodore L. Willke3 ([email protected]), and Jonathan D. Cohen1 ([email protected]) 1Princeton Neuroscience Institute, Princeton University 2Department of Mechanical and Aerospace Engineering, Princeton University 3Parallel Computing Lab, Intel Corporation
منابع مشابه
Performance of the Wavelet Transform-Neural Network Based Receiver for DPIM in Diffuse Indoor Optical Wireless Links in Presence of Artificial Light Interference
Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both doma...
متن کاملForward kinematic analysis of planar parallel robots using a neural network-based approach optimized by machine learning
The forward kinematic problem of parallel robots is always considered as a challenge in the field of parallel robots due to the obtained nonlinear system of equations. In this paper, the forward kinematic problem of planar parallel robots in their workspace is investigated using a neural network based approach. In order to increase the accuracy of this method, the workspace of the parallel robo...
متن کاملآموزش شبکه عصبی MLP در فشردهسازی تصاویر با استفاده از روش GSA
Image compression is one of the important research fields in image processing. Up to now, different methods are presented for image compression. Neural network is one of these methods that has represented its good performance in many applications. The usual method in training of neural networks is error back propagation method that its drawbacks are late convergence and stopping in points of lo...
متن کاملA Hybrid Neural Network Approach for Kinematic Modeling of a Novel 6-UPS Parallel Human-Like Mastication Robot
Introduction we aimed to introduce a 6-universal-prismatic-spherical (UPS) parallel mechanism for the human jaw motion and theoretically evaluate its kinematic problem. We proposed a strategy to provide a fast and accurate solution to the kinematic problem. The proposed strategy could accelerate the process of solution-finding for the direct kinematic problem by reducing the number of required ...
متن کاملNeural Networks for fast sensor data processing in Laser Welding
To address the need for robust and fast representation, we introduce deep learning neural networks and parallel programming techniques for laser welding. In order to deal with high-dimensional data within real-time constraints, we use a deep autoencoder to extract robust, meaningful and low dimensional features. The implementation is then optimized, using parallel programming techniques and sho...
متن کامل