
The paper deals with pseudorandom generators based on complexity considerations (good generators are characterized via some abstract computation or circuit complexity properties called hardness) rather than on the probabilistic investigations. It contains mainly the results of the authors presented on several conferences and requires knowledge of many papers mentioned in the introduction. After a quite long discussion of known results the authors show that the pseudorandom generators using the XOR lemma allowing hardness amplification [cf. \textit{N. Nissan} and \textit{A. Widgerson}, J.Comput. Syst. Sci. 49, No.~2, 149-167 (1994; Zbl 0821.68057)] can be modified via the application of pseudoentropy generators introduced by the authors. The authors are able to find a new type of pseudorandom generators based on the concept of hardness and to find new results and new proofs of known ones (e.g. the connection between the hardness amplification and a list decoding algorithm for error correcting codes and the derivation of a list correcting algorithm for error correcting codes based on multivariate polynomials). The paper is very technical and is based on the results of more than fifty papers. It contains no computer programs of the discussed algorithms and no statistical tests of the proposed generators. It is not too clear whether the generators presented in the paper are easily implementable and/or usable.
Pseudo-random numbers; Monte Carlo methods, Computer Networks and Communications, Analysis of algorithms and problem complexity, Applied Mathematics, hardness amplification, polynomial reconstruction, pseudoergodic generator, circuit complexity, 004, Theoretical Computer Science, pseudorandom number generation, Complexity and performance of numerical algorithms, Computational Theory and Mathematics, pseudorandom generators, error correcting codes, Random number generation in numerical analysis, list decoding, extractors
Pseudo-random numbers; Monte Carlo methods, Computer Networks and Communications, Analysis of algorithms and problem complexity, Applied Mathematics, hardness amplification, polynomial reconstruction, pseudoergodic generator, circuit complexity, 004, Theoretical Computer Science, pseudorandom number generation, Complexity and performance of numerical algorithms, Computational Theory and Mathematics, pseudorandom generators, error correcting codes, Random number generation in numerical analysis, list decoding, extractors
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