in this paper, we introduce a takagi-sugeno (ts) fuzzy model which is derived from a typical multi-layer perceptron neural network (mlp nn). at first, it is shown that the considered mlp nn can be interpreted as a variety of ts fuzzy model. it is discussed that the utilized membership function (mf) in such ts fuzzy model, despite its flexible structure, has some major restrictions. after modify...

Cancer has become a major adversary to human health and the development and enhancement of techniques for use in its diagnosis and treatment have quickly become a focus of worldwide research. In recent years, Fourier transform infrared (FTIR) spectroscopy has been increasingly applied to the study of biomedical conditions and is becoming a powerful tool for determining the biochemical compositi...

We initiate a study of Maurer’s bounded storage model (JoC, 1992) in presence of transmission errors and perhaps other types of errors that cause different parties to have inconsistent views of the public random source. Such errors seem inevitable in any implementation of the model. All previous schemes and protocols in the model assume a perfectly consistent view of the public source from all ...

We consider a generalized adaptive and active adversary model for unconditionally secure Multi-Party Computation (MPC) in the zero error case. Cramer et al. proposed a generic approach to build a multiplicative Monotone Span Programs (MSP) – the special property of a Linear Secret Sharing Schemes (LSSS) that is needed to perform a multiplication of shared values. They give an efficient generic ...

While there is a great deal of sophistication in modern cryptology, simple (and simplistic) explanations of cryptography remain useful and perhaps necessary. Many of the explanations are informal; others are embodied in formal methods, particularly in formal methods for the analysis of security protocols. This note (intended to accompany a talk at the Crypto 2000 conference) describes some of t...

We propose a method for upper bounding the general adversary bound for certain boolean functions. Due to the the tightness of query complexity and the general adversary bound [5], this gives an upper bound on the quantum query complexity of those functions. We give an example where this upper bound is smaller than the query complexity of any known quantum algorithm.