The human ability to understand speech is underpinned by a hierarchical auditory system whose successive stages process increasingly complex attributes of the acoustic input. It has been suggested that to produce categorical speech perception, this system must elicit consistent neural responses to speech tokens (e.g., phonemes) despite variations in their acoustics. Here, using electroencephalo...

When multiple geo-spatial datasets are integrated, the process should be done in several stages. In each stage two datasets are fused to one. Since different sequences may lead to different results, it is important to select a sequence that would lead to the required results. Two approaches, namely the sequential and hierarchical, for selecting the sequence are presented, and their results are ...

We propose a hierarchical Bayesian model the wordless Hierarchical Dirichlet Processes-Hidden Markov Model (wHDP-HMM), to tackle the problem of unsupervised cell phenotype clustering during the mitosis stages. Our model combines the unsupervised clustering capabilities of the HDP model with the temporal modeling aspect of the HMM. Furthermore, to model cell phenotypes effectively, our model use...

Barring any cancer prevention breakthroughs, the expansion of the aged population will likely increase number of older individuals diagnosed for cancer in the coming decades. Dimensions of the cancer burden and its devastating manner of challenge ahead are inferred in the context of with aging populations to underscore the possible increase that demographic factors may have on the magnitude of ...

In this contribution we propose a hierarchical intonation model for synthesising f0 contours with application to text-to-speech synthesis in Galician language. This model makes use of the implicit knowledge that resides in a database of natural f0 contours obtained from a read corpus. The novelty of this method lies on the way the f0 contour is generated. First, no phonological description in t...

Learning sparse representations on data adaptive dictionaries is a state-of-the-art method for modeling data. But when the dictionary is large and the data dimension is high, it is a computationally challenging problem. We explore three aspects of the problem. First, we derive new, greatly improved screening tests that quickly identify codewords that are guaranteed to have zero weights. Second,...

We observed that before initiating software development the objectives are minimally organized and developers introduce comparatively higher organization throughout the design process. To be able to formally capture this observation, a new communication channel representation system for software is developed in three stages a) set-theoretical representation of software design, b) mapping of sof...

We derive a continuous cost function for hierarchical clustering that is amenable to gradient-based optimization. Our continuous cost function is inspired by a recently proposed, discrete hierarchical cost function [5]. We present an accompanying algorithm that proceeds in two stages. In the first stage, the algorithm learns parametric routing functions at each node in a fixed hierarchy. In the...

The paper introduces a reinforcement learning-based methodology for performance improvement of Intelligent Controllers. The translation interfaces of a 3-level Hierarchical Goal-Directed Intelligent Machine (HGDIM) are modeled by a 2-stage Hierarchical Learning Stochas-tic Automaton (HLSA). The decision probabilities at the two stages are recursively updated from the success and failure signals...

Ensuring that the appropriate level of security is available in wireless networks is absolutely essential. To aid in the defense and detection of potential threats, WLANs should employ security solutions that include an anomaly-based intrusion detection system (ADS) that identify wireless network intrusions by gathering and analyzing the data that is available on the system. This paper is to pr...