The trust value based on fuzzy comprehensive evaluation fluctuates remarkably. Aiming at this problem, this paper establishes membership function of trusted set, according to the trusted level in P2P trust model based on fuzzy comprehensive evaluation. The simulation results and analysis show that the membership function of trusted set can validate whether the trust evaluation value is sufficie...

A neural network is an information processing system that is widely used in various computer vision applications. This paper discusses an low-latency FPGA-based neural network implementation that does direct computation of the sigmoid activation function.

This paper shows that the performance of the Hoppeld network for solving optimization problems can be improved by using a new activation (output) function. The eeects of the activation function on the performance of the Hoppeld network are analyzed. It is shown that the sigmoid activation function in the Hoppeld network is sensitive to noise of neurons. The reason is that the sigmoid function i...

We present a methodology for characterization and an approach for computing the solutions of fuzzy linear systems with LR fuzzy variables. As solutions, notions of exact and approximate solutions are considered. We transform the fuzzy linear system into a corresponding linear crisp system and a constrained least squares problem. If the corresponding crisp system is incompatible, then the fuzzy ...

-The sigmoid fimction & very widely used as a neuron activation fimction in artificial neural networks. which makes its attributes a matter o f some interest. This paper presents some general results on the derivatives o f the sigmoid. These results relate the coefficients o f various derivatives to standard number sequences from combinatorial theory, and thus provide a standard efficient way o...

this paper presents a fuzzy goal programming (fgp) methodology for solving bi-level quadratic programming (blqp) problems. in the fgp model formulation, firstly the objectives are transformed into fuzzy goals (membership functions) by means of assigning an aspiration level to each of them, and suitable membership function is defined for each objectives, and also the membership functions for vec...

Measurement results contain different kinds of uncertainty. Besides systematic errors andrandom errors individual measurement results are also subject to another type of uncertainty,so-called emph{fuzziness}. It turns out that special fuzzy subsets of the set of real numbers $RR$are useful to model fuzziness of measurement results. These fuzzy subsets $x^*$ are called emph{fuzzy numbers}. The m...