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In this study, a neural network (NN) based dynamic Mach number predictive control was proposed for a wind tunnel Match number control system. The proposed method absorbed in advantages both artificial neural network and model predictive control, for control of strong nonlinear, multiple variables, large lagging, and time-varying system. In this approach, the dynamic of wind tunnel is represented by...
The 2.4m×2.4m wind tunnel is a system with the properties of strong nonlinear, multiple variables, serious coupling, large lagging, time-varying, etc. The complexity of all these phenomena makes the development of suitable dynamic Mach number models based on the aerodynamics laws very difficult. As an alternative, the Ensemble Neural Networks (ENN) model based on the feature subsets is proposed to...
A new logical method based on game to model and analyze electronic payment protocols is proposed in this paper. Strict formal analysis for Bolignano protocol is made by this new method, and Bolignano protocol is discovered non-fairness. These works indicate that the ATL logic based on game is more suitable to describe and analyze electronic payment protocols than traditional CTL.
In this paper Shuffled Frog Leaping Algorithm based neural network is used in speech emotion recognition. Speech emotion data is collected and emotional features are analyzed. Shuffled Frog Leaping Algorithm is used to train the random initial data, optimize the connection weights and thresholds of the neural network with a fast network convergence speed. The results show that Shuffled Frog Leaping...
This paper proposes a modified Gaussian Mixed Model (GMM) with an embedded Time Delay Neural Network (TDNN). It integrates the merits of GMM which is a generative model and TDNN which is a discriminative model. TDNN digests the timing information of the feature sequences, and through the transformation of the feature vectors it makes the hypothesis of variable independence that maximum likelihood...
This paper proposes a modified gaussian mixed model (GMM) with an embedded auto-associate neural network (AANN). It integrates the merits of GMM and AANN. GMM and AANN are trained as a whole by means of maximum likelihood. In the process of training, the parameter of GMM and AANN are updated alternately. AANN reshapes the distribution of the data and improves the similarity of the data in one class...
To model fuzzy dynamic capacity acquisition and assignment, the paper considers a fuzzy expected value model based on credibility theory and two-stage fuzzy optimization method. After that, a solution approach, which combines fuzzy simulations, neural network (NN) and genetic algorithm (GA), is designed to solve this proposed two-stage fuzzy dynamic capacity acquisition and assignment problem. At...
Frequency offsets in regular OFDM communication systems distort the orthogonality between sub-carriers, which results in inter-carrier interference (ICI). In order to combat the impact of ICI on OFDM systems, an ICI mitigation technique by jointing symbol shift cancellation (SSC) and adjacent sub-channel filter (ASF) is proposed in this paper. At first, the symbol shift cancellation method is used...
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