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This paper proposes a cyclic steganographic scheme based on cyclic codes for embedding secret message. This scheme is capable of achieving low complexity and fast embedding time. These are two attractive reasons for this method: first, embedding and secret message extraction can be implemented easily by employing shift registers with feedback connections, and second, because they are rich in coding...
This study proposes a Spread Spectrum Clock Generator (SSCG) for Serial-ATA II, which is realized by a delta-sigma fractional-N frequency synthesizer with a digital triangular profile generator without external clock and a half-integer divider. By adding only a negative-edge-triggered resampler and using phase combination technique, the half-integer divider can be realized by any kind of integer programmable...
We present a new reseeding-mixing method to extend the system period length and to enhance the statistical properties of a chaos-based logistic map pseudo random number generator (PRNG). The reseeding method removes the short periods of the digitized logistic map and the mixing method extends the system period length to by “xoring” with a DX generator. When implemented in the TSMC 0.18- ...
This paper proposes a self-reseeding pseudo RNG (PRNG) based on digitized logistic map to introduce small perturbations periodically so that the low-period can be removed and the randomness can be enhanced. The strategy and the optimization of selecting reseeding period with corresponding fixed pattern are demonstrated. The resultant PRNG generates random sequence fulfilling all the randomness requirements...
In recent years, many researchers have proposed several algorithms to schedule critical tasks in a homogeneous multiprocessor system for obtaining a shorter scheduling length. However, for heterogeneous computing systems, such methods may lead to lengthen the execution of other non-critical tasks. In this paper, a Non-critical Path Earliest-Finish (NPEF) scheduling algorithm for heterogeneous computing...
This paper presents development of an automatic fault diagnosis system in the nuclear power plants to minimize possible nuclear disasters caused by inaccurate diagnoses done by operators. Combined binary and decimal coding methods are employed in this work based on radial basis function neural network (RBFNN) structure. This underling RBFNN structure is further trained through genetic optimization...
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