Computer Technology and Computer Programming: New Research - download pdf or read online

By James L. Antonakos

Protecting a huge diversity of latest issues in machine know-how and programming, this quantity discusses encryption strategies, SQL iteration, net 2.0 applied sciences, and visible sensor networks. It additionally examines reconfigurable computing, video streaming, animation recommendations, and extra. Readers will find out about an instructional software and online game to aid scholars research laptop programming. The ebook additionally explores a brand new scientific expertise paradigm headquartered on instant expertise and cloud computing designed to beat the issues of accelerating future health know-how charges.

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V. Dudul, “Identification of a liquid saturated steam heat exchanger using focused time lagged recurrent neural network model,” IETE Journal of Research, vol. 53, no. 1, pp. 69–82, 2007. 15. A. R. Barron, “Universal approximation bounds for superpositions of a sigmoidal function,” IEEE Transactions on Information Theory, vol. 39, no. 3, pp. 930–945, 1993. 16. A. Juditsky, H. Hjalmarson, A. , “Nonlinear black-box models in system identification: mathematical foundations,” Automatica, vol. 31, no.

Implementation of three different tasks (executed by one or several CEs) using a mesh network. A truly regular mesh is based on the assumption that the FPGA is intrinsically homogeneous. So, every CE presents the same hardware properties for task implementation. Considering the heterogeneous structure of available FPGAs, it seems quite difficult to implement a truly regular mesh. Finally, another problem of the mesh structure lies in the connection of shared elements like memories or IOs. Indeed, the communication requirements between tasks (hardware or software) and shared elements induce the creation of hot-spots, which could increase the likelihood of livelock and deadlock.

Novel FTLRNN with Gamma Memory for Short-Term and Long-Term 49 31. F. M. Ham and I. Kostanic, Principles of Neurocomputing for Science and Engineering, Tata McGraw-Hill, New Delhi, India, 2002. 32. B. de Vries and J. C. Principe, “The gamma model—a new neural model for temporal processing,” Neural Networks, vol. 5, no. 4, pp. 565–576, 1992. 33. J. C. Principe and N. R. Euliano, Neural and Adaptive Systems: Fundamental through Simulations, John Wiley & Sons, New York, NY, USA, 2000. 34. M. C. Mackey and L.

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