Search results for "HIDDEN"

Gesture Modeling by Hanklet-Based Hidden Markov Model

2015

In this paper we propose a novel approach for gesture modeling. We aim at decomposing a gesture into sub-trajectories that are the output of a sequence of atomic linear time invariant (LTI) systems, and we use a Hidden Markov Model to model the transitions from the LTI system to another. For this purpose, we represent the human body motion in a temporal window as a set of body joint trajectories that we assume are the output of an LTI system. We describe the set of trajectories in a temporal window by the corresponding Hankel matrix (Hanklet), which embeds the observability matrix of the LTI system that produced it. We train a set of HMMs (one for each gesture class) with a discriminative a…

Harmony perception and regularity of spike trains in a simple auditory model

2013

A probabilistic approach for investigating the phenomena of dissonance and consonance in a simple auditory sensory model, composed by two sensory neurons and one interneuron, is presented. We calculated the interneuron’s firing statistics, that is the interspike interval statistics of the spike train at the output of the interneuron, for consonant and dissonant inputs in the presence of additional "noise", representing random signals from other, nearby neurons and from the environment. We find that blurry interspike interval distributions (ISIDs) characterize dissonant accords, while quite regular ISIDs characterize consonant accords. The informational entropy of the non-Markov spike train …

Hidden oscillations in SPICE simulation of two-phase Costas loop with non-linear VCO

2016

Simulation is widely used for analysis of Costas loop based circuits. However it may be a non-trivial task, because incorrect choice of integration parameters may lead to qualitatively wrong conclusions. In this work the importance of choosing appropriate parameters and simulation model is discussed. It is shown that hidden oscillations may not be found by simulation in SPICE, however it can be predicted by analytical methods. peerReviewed

The Keeper of the Salt. Hidden economy and clash of jurisdiction in the Valley of Cofrentes in the mid XVIIIth Century

2006

La muerte violenta de un guardia de la real renta de salinas en un barranco de Cofrentes, en febrero de 1747, puso al descubierto la existencia de una fábrica clandestina y de una red de contrabando de sal que abastecía a numerosos conventos valencianos. Dos factores coyunturales propiciaron su aparición: las dificultades de suministro de uno de los principales alfolíes reales y el impuesto extraordinario fijado sobre el precio de la sal con motivo de la guerra de Sucesión austríaca. Pero, al margen de ello, el caso revela las carencias estructurales del aparato de vigilancia y las contradicciones entre los distintos ámbitos jurisdiccionales implicados, que hicieron posible la articulación …

Probabilistic techniques for bridging the semantic gap in schema alignment

Connecting pieces of informations from heterogeneous sources sharing the same domain is an open challenge in Semantic Web, Big Data and business communities. The main problem in this research area is to bridge the expressiveness gap between relational databases and ontologies. In general, an ontology is more expressive and captures more semantic information behind data than a relational database does. On the other side, databases are the most common used persistent storage system and they grant benefits such as security and data integrity but they need to be managed by expert users. The problem is quite significant above all when enterprise or corporate ontologies are used to share infomation…

Hidden Markov random field model and Broyden–Fletcher–Goldfarb–Shanno algorithm for brain image segmentation

2018

International audience; Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of medical images, the manual analysis and interpretation became a tedious task. Thus, automatic image segmentation became essential for diagnosis assistance. Segmentation consists in dividing the image into homogeneous and significant regions. We focus on hidden Markov random fields referred to as HMRF to model the problem of segmentation. This modelisation leads to a classical function minimisation problem. Broyden-Fletcher-Goldfarb-Shanno algorithm referred to as BFGS is one of the most powerful methods to solve unconstrained optimisation problem. …

Vector representation of non-standard spellings using dynamic time warping and a denoising autoencoder

2017

The presence of non-standard spellings in Twitter causes challenges for many natural language processing tasks. Traditional approaches mainly regard the problem as a translation, spell checking, or speech recognition problem. This paper proposes a method that represents the stochastic relationship between words and their non-standard versions in real vectors. The method uses dynamic time warping to preprocess the non-standard spellings and autoencoder to derive the vector representation. The derived vectors encode word patterns and the Euclidean distance between the vectors represents a distance in the word space that challenges the prevailing edit distance. After training the autoencoder o…

The dynamic interdependence in the demand of primary and emergency secondary care: A hidden Markov approach

2021

This paper develops an extension of the class of finite mixture models for longitudinal count data to the bivariate case by using a trivariate reduction technique and a hidden Markov chain approach. The model allows for disentangling unobservable time-varying heterogeneity from the dynamic effect of utilisation of primary and secondary care and measuring their potential substitution effect. Three points of supports adequately describe the distribution of the latent states suggesting the existence of three profiles of low, medium and high users who shows persistency in their behaviour, but not permanence as some switch to their neighbour's profile.

CAD-Based Training of an Expert System and a Hidden Markov Model for Obstacle Detection in an Industrial Robot Environment

2012

Abstract Deploying industrial robots in harsh outdoor environments require additional functionalities not currently provided. For instance, movement of standard industrial robots are pre-programmed to avoid collision. In dynamic and less structured environments, however, the need for online detection and avoidance of unmodelled objects arises. This paper focus on online obstacle detection using a laser sensor by proposing three different approaches, namely a CAD-based Expert System (ES) and two probabilistic methods based on a Hidden Markov Model (HMM) which requires observation based training. In addition, this paper contributes by providing a comparison between the CAD-based ES and the tw…

Using Hankel matrices for dynamics-based facial emotion recognition and pain detection

2015

This paper proposes a new approach to model the temporal dynamics of a sequence of facial expressions. To this purpose, a sequence of Face Image Descriptors (FID) is regarded as the output of a Linear Time Invariant (LTI) system. The temporal dynamics of such sequence of descriptors are represented by means of a Hankel matrix. The paper presents different strategies to compute dynamics-based representation of a sequence of FID, and reports classification accuracy values of the proposed representations within different standard classification frameworks. The representations have been validated in two very challenging application domains: emotion recognition and pain detection. Experiments on…