Statistical guarantees of performance for MIMO designs

Kumar, Jayanand Asok; Vasudevan, Shobha

doi:10.1109/dsn.2010.5544281

Cited by 6 publications

References 110 publications

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E-commerce Recommendation Method Based on Genetic Algorithm and Composite Weight Matrix

Liang

2010

2010 International Conference on Electrical and Control Engineering

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Accounting for the characteristics of E-commerce Website personal service and the features of users' and goods' similarities distribution, an E-commerce recommendation method based on clustering using genetic algorithm is designed. By using a composite weight matrix to integrate the situation of users purchasing, this method improves the result of clustering , and the result of clustering reflects the similarities of users and goods more accurately. This method is accorded with the reality of E-commerce Website personal service and is perfect for users' and goods' clustering computing on E-commerce Website recommendation.

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E-commerce Recommendation Method Based on Genetic Algorithm and Composite Weight Matrix

Liang

2010

2010 International Conference on Electrical and Control Engineering

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Probabilistic model checking of single event transient propagation at RTL level

Hamad

Mohamed

Savaria

2014

2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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Soft errors, induced by radiations, have a growing impact on the reliability of CMOS integrated circuits. The progressive shrinking of device sizes in advanced technologies leads to miniaturization and performance improvements. However, ultra-deep sub-micron technologies are more vulnerable to soft errors. In this paper, we propose a new methodology to model and analyze Single Event Transients (SETs) propagation at RTL level. Gate level characterization libraries are utilized to model the underlying probabilistic behavior of SET pulse propagation as Probabilistic Automata (PA). A probabilistic model checker is adapted to analyze the probability of SET pulse propagation for all injection scenarios. Experimental results are presented for different combinational circuits. Our proposed methodology is orders of magnitude faster than contemporary techniques that can be used to analyze SET pulse propagation probability.

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