Search results for "Neural"
showing 10 items of 2783 documents
Synchronization of Uncertain Neural Networks with H8 Performance and Mixed Time-Delays
2011
An exponential H8 synchronization method is addressed for a class of uncertain master and slave neural networks with mixed time-delays, where the mixed delays comprise different neutral, discrete and distributed time-delays. An appropriate discretized Lyapunov-Krasovskii functional and some free weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing a delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H8 synchronization of the two coupled master and slave neural networks regardless of their initial states. Numerical simulatio…
Notice of Violation of IEEE Publication Principles: New Delay-Dependent Exponential $H_{\infty}$ Synchronization for Uncertain Neural Networks With M…
2010
This paper establishes an exponential H infin synchronization method for a class of uncertain master and slave neural networks (MSNNs) with mixed time delays, where the mixed delays comprise different neutral, discrete, and distributed time delays. The polytopic and the norm-bounded uncertainties are separately taken into consideration. An appropriate discretized Lyapunov-Krasovskii functional and some free-weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H infin synchr…
Investigation of Tinnitus Patients in Italy: Clinical and Audiological Characteristics
2010
Objective. 312 tinnitus sufferers were studied in order to analyze: the clinical characteristics of tinnitus; the presence of tinnitus-age correlation and tinnitus-hearing loss correlation; the impact of tinnitus on subjects' life and where possible the etiological/predisposing factors of tinnitus.Results. There is a slight predominance of males. The highest percentage of tinnitus results in the decades 61–70. Of the tinnitus sufferers, 197 (63.14%) have a hearing deficit (light hearing loss in 37.18% of cases). The hearing impairment results of sensorineural type in 74.62% and limited to the high frequencies in 58.50%. The tinnitus is referred as unilateral in 59.93%, a pure tone in 66.99%…
Sunct syndrome. Report of a case and treatment update
2015
Short-lasting unilateral neuralgiform headache attacks with conjuntival injection and tearing (SUNCT) is considered a rare trigeminal autonomic cephalgias, a group of primary headache disorders characterized by brief episodes of severe unilateral headache in the distribution territory of the trigeminal nerve, accompanied by prominent ipsilateral and cranial parasympathetic autonomic features. The present report describes a SUNCT syndrome in a 64-year-old male who had been diagnosed with trigeminal neuralgia several years ago. The patient reported stabbing pain in the orbital zone and in the left upper maxillary region, of great intensity, brief duration, and a frequency of 20-100 attacks a …
Computer-Aided Diagnosis System with Backpropagation Artificial Neural Network—Improving Human Readers Performance
2016
This article presents the results of a study into possibility of artificial neural networks (ANNs) to classify cancer changes in mammographic images. Today’s Computer-Aided Detection (CAD) systems cannot detect 100 % of pathological changes. One of the properties of an ANN is generalized information —it can identify not only learned data but also data that is similar to training set. The combination of CAD and ANN could give better result and help radiologists to take the right decision.
Multilayer neural networks: an experimental evaluation of on-line training methods
2004
Artificial neural networks (ANN) are inspired by the structure of biological neural networks and their ability to integrate knowledge and learning. In ANN training, the objective is to minimize the error over the training set. The most popular method for training these networks is back propagation, a gradient descent technique. Other non-linear optimization methods such as conjugate directions set or conjugate gradient have also been used for this purpose. Recently, metaheuristics such as simulated annealing, genetic algorithms or tabu search have been also adapted to this context.There are situations in which the necessary training data are being generated in real time and, an extensive tr…
Towards to deep neural network application with limited training data: synthesis of melanoma's diffuse reflectance spectral images
2019
The goal of our study is to train artificial neural networks (ANN) using multispectral images of melanoma. Since the number of multispectral images of melanomas is limited, we offer to synthesize them from multispectral images of benign skin lesions. We used the previously created melanoma diagnostic criterion p'. This criterion is calculated from multispectral images of skin lesions captured under 526nm, 663nm, and 964nm LED illumination. We synthesize these three images from multispectral images of nevus so that the p' map matches the melanoma criteria (the values in the lesion area is >1, respectively). Demonstrated results show that by transforming multispectral images of benign nevus i…
High resolution mouse subventricular zone stem cell niche transcriptome reveals features of lineage, anatomy, and aging
2020
AbstractAdult neural stem cells (NSC) serve as a reservoir for brain plasticity and origin for certain gliomas. Lineage tracing and genomic approaches have portrayed complex underlying heterogeneity within the major anatomical location for NSC, the subventricular zone (SVZ). To gain a comprehensive profile of NSC heterogeneity, we utilized a well validated stem/progenitor specific reporter transgene in concert with single cell RNA sequencing to achieve unbiased analysis of SVZ cells from infancy to advanced age. The magnitude and high specificity of the resulting transcriptional data sets allow precise identification of the varied cell types embedded in the SVZ including specialized parench…
Resolving the transcriptional transitions associated with oligodendrocyte generation from adult neural stem cells by single cell sequencing
2020
AbstractThe subventricular zone (SVZ) is the largest neurogenic niche in the adult forebrain. Notably, neural stem cells (NSCs) of the SVZ generate not only neurons, but also oligodendrocytes, the myelin-forming cells of the central nervous system. Transcriptomic studies have provided detailed knowledge of the molecular events that regulate neurogenesis, but little is understood about adult oligodendrogenesis from SVZ-NSCs. To address this, we performed in-depth single-cell transcriptomic analyses to resolve the major differences in neuronal and oligodendroglial lineages derived from the adult SVZ. A hallmark of adult oligodendrogenesis was the stage-specific expression of transcriptional m…
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance
2020
We present a pairwise learning to rank approach based on a neural net, called DirectRanker, that generalizes the RankNet architecture. We show mathematically that our model is reflexive, antisymmetric, and transitive allowing for simplified training and improved performance. Experimental results on the LETOR MSLR-WEB10K, MQ2007 and MQ2008 datasets show that our model outperforms numerous state-of-the-art methods, while being inherently simpler in structure and using a pairwise approach only.