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Recurrent neural networks with various types of hidden units have been used to solve a diverse range of problems involving sequence data. Two of the most recent proposals, gated recurrent units (GRU) and minimal gated units (MGU), have shown comparable promising results on example public datasets. In this paper, we introduce three model variants of the minimal gated unit which further simplify that...
This paper introduces the architecture and learning procedure of dynamic adaptive neuro-fuzzy inference system (DANFIS) for nonlinear dynamical system modeling. In our DANIS model, IF part of the rules are comprised of Gaussian type membership functions and THEN part of the rules are differential equations of linear functions. In order to find optimal model parameters, a gradient based algorithm Broyden-Fletcher-Goldfarb-Shanno...
In order to meet the demand of visual behavior recognition, we introduce Fractal Conditional Random Field (FCRF) model. FCRF model has improved Latent-Dynamic Conditional Random Field (LDCRF), and proposed the concept of fractal labels that define the integrity and directionality of human behavior. FCRF model overcomes real-time issues of the Hidden Conditional Random Field (HCRF) and the problem...
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