M. Amin Shokrollahi

Practical loss-resilient codes

We present randomized constructions of linear-time encodable and decodable codes that can transmit over lossy channels at rates extremely close to capacity. The encod-ing and decoding algorithms for these codes have fast and simple software implementations. Partial implementationsof our algorithms are faster by orders of magnitude than the best software implementations of any previous algorithm forthis problem. We expect these codes will be extremely useful for applications such as real-time audio and video transmission over the Internet, where lossy channels are common and fast decoding is a requirement. Despite the simplicity of the algorithms, their design andanalysis are mathematically intricate. The design requires the careful choice of a random irregular bipartite graph,where the structure of the irregular graph is extremely important. We model the progress of the decoding algorithmby a set of differential equations. The solution to these equations can then be expressed as polynomials in one variable with coefficients determined by the graph structure. Based on these polynomials, we design a graph structure that guarantees successful decoding with high probability

Normal bases via general Gauss periods

Gauss periods have been used successfully as a tool for constructing normal bases in finite fields. Starting from a primitive

Fast and precise computations of discrete Fourier transforms using cyclotomic integers

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Analysis of random processes via And-Or tree evaluation

th root of unity, one obtains under certain conditions a normal basis for

Multi-stage code generator and decoder for communication systems

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Systematic encoding and decoding of chain reaction codes

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Forward error-correcting (fec) coding and streaming

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File download and streaming system

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Multiple-field based code generator and decoder for communications systems

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Method and apparatus for fast encoding of data symbols according to half-weight codes

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