A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability parameters are replaced by the outputs of state-specific neural networks. As opposed to many othe...

Quasi-HNN groups can be characterized as a generalization of HNN groups. In this paper, we show that if G * is a quasi-HNN group of base G, then either any two conjugates of G are identical or their intersection is contained in a conjugate of an associated subgroup of G.

By improving the previous construction in [18] we observe that any reduced HNN extension is a corner of a certain reduced amalgamated free product in both the von Neumann algebra and the C∗-algebra settings. Then, the same fact is shown for universal HNN extensions of C∗-algebras. We apply the observation to the questions of factoriality and type classification of HNN extensions of von Neumann ...

This paper proposes a novel Hermite neural network-based second-order sliding-mode (HNN-SOSM) control strategy for the synchronous reluctance motor (SynRM) drive system. The proposed HNN-SOSM is nonlinear vector consisting of speed loop and current loop. adopts composite controller, which composed three components: 1) standard super-twisting algorithm-based SOSM (STA-SOSM) controller achieving ...

THE concept of HNN-extensions of groups was introduced by Higman, Neumann and Neumann in 1949. HNN-extensions and amalgamated free products have played a crucial role in combinatorial group theory, especially for algorithmic problems. In inverse semigroup theory there are many ways of constructing HNNextension in order to ensure the embeddability of the original inverse semigroup in the new one...

The enhancement of Hopfield Neural Network (HNN) multiuser detector for Multicarrier CodeDivision Multiple-Access (MC-CDMA) signals in a multipath fading channel (MPF) is investigated. The previous design of HNN fails to remove Multiple-Access Interference (MAI) in a MPF channel because it is designed to work in a Gaussian channel. In this paper, we have designed a new HNN multiuser detector th...

This study proposed a hybridization of higher-order Random Boolean kSatisfiability (RANkSAT) with the Hopfield neural network (HNN) as neuro-dynamical model designed to reflect knowledge efficiently. The learning process has undergone significant changes and improvements according various types optimization problems. However, HNN is associated some limitations which include storage capacity bei...

This paper proposes a novel two-stage hypergraph-based framework, dubbed ADaptive Hypergraph Neural Network (AD-HNN) to estimate multiple human poses from single image, with keypoint localization network and an Adaptive-Pose (AP-HNN) added onto the former network. For providing better guided representations of AP-HNN, we employ Semantic Interaction Convolution (SIC) module within initial acquir...

We give a criterion for an HNN extension of a finite p-group to be residually p. 1. Statement of the Main Results By an HNN pair we mean a pair (G,φ) where G is a group and φ : A → B is an isomorphism between subgroups A and B of G. Given such an HNN pair (G,φ) we consider the corresponding HNN extension G∗ = 〈G, t | t−1at = φ(a), a ∈ A〉 of G, which we denote, by slight abuse of notation, as G∗...

The GTPase ARL13B is localized to primary cilia; small cellular protrusions that act as antennae. Its defective ARL13B hennin (HNN) variant is linked causally with Joubert Syndrome, a developmental ciliopathy attributed to poor sensing of extracellular chemical gradients. We tested the hypothesis that impaired detection of extracellular voltage gradients also contributes to the HNN phenotype. I...