نتایج جستجو برای: data decoding

تعداد نتایج: 2427558  

Journal: :CoRR 2005
Pascal O. Vontobel Ralf Koetter

The goal of the present paper is the derivation of a framework for the finite-length analysis of message-passing iterative decoding of low-density parity-check codes. To this end we introduce the concept of graph-cover decoding. Whereas in maximum-likelihood decoding all codewords in a code are competing to be the best explanation of the received vector, under graph-cover decoding all codewords...

Journal: :IEEE Trans. Med. Imaging 2003
Gloria Menegaz Jean-Philippe Thiran

We propose a fully three-dimensional wavelet-based coding system featuring 3D encoding/2D decoding functionalities. A fully threedimensional transform is combined with context adaptive arithmetic coding; 2D decoding is enabled by encoding every 2D subband image independently. The system allows a finely graded up to lossless quality scalability on any 2D image of the dataset. Fast access to 2D i...

Journal: :RFC 1981
Alan R. Katz

This note describes the implementation of a program to decode facsimile data from the Rapicom 450 facsimile (fax) machine into an ordinary bitmap. This bitmap can then be displayed on other devices or edited and then encoded back into the Rapicom 450 format. In order to do this, it was necessary to understand the how the encoding/decoding process works within the fax machine and to duplicate th...

2007
Candy Goyal Isha sood Isha Sood

With shrinking feature size and increasing frequency, power dissipation on data bus has become the most predominant factor than the power dissipation in other parts of the circuitry. The large intrinsic capacitance associated with buses is responsible for a substantial fraction (approx 40%) of total power dissipated, because the bus power dissipation is proportional to switching activity. The m...

2017
Erik Rybakken Nils Baas Benjamin Dunn

We introduce a novel data-driven approach to discover and decode features in the neural code coming from large population neural recordings with minimal assumptions, using cohomological learning. We apply our approach to neural recordings of mice moving freely in a box, where we find a circular feature. We then observe that the decoded value corresponds well to the head direction of the mouse. ...

Journal: :IEEE Transactions on Intelligent Transportation Systems 2020

Journal: :International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 2014

Journal: :Proceedings of the AAAI Conference on Artificial Intelligence 2020

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