Results 131 to 140 of about 99,773 (316)

Applications of recurrent neural networks in batch reactors. Part II: Nonlinear inverse and predictive control of the heat transfer fluid temperature [PDF]

open access: yes, 1998
Although nonlinear inverse and predictive control techniques based on artificial neural networks have been extensively applied to nonlinear systems, their use in real time applications is generally limited.
Zaldívar, J.M., Galván, Inés M.
core   +1 more source

Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett   +8 more
wiley   +1 more source

Self-Optimization in Continuous-Time Recurrent Neural Networks

open access: yesFrontiers in Robotics and AI, 2018
A recent advance in complex adaptive systems has revealed a new unsupervised learning technique called self-modeling or self-optimization. Basically, a complex network that can form an associative memory of the state configurations of the attractors on ...
Mario Zarco, Tom Froese, Tom Froese
doaj   +1 more source

Synchronization of coupled neutral-type neural networks with jumping-mode-dependent discrete and unbounded distributed delays

open access: yes, 2013
This is the post-print version of the Article. The official published version can be accessed from the links below - Copyright @ 2013 IEEE.In this paper, the synchronization problem is studied for an array of N identical delayed neutral-type neural ...
Liu, Y   +11 more
core   +1 more source

Structure–Function Decoupling of the Sensorimotor and Default Mode Networks in Black Americans With MS

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano   +11 more
wiley   +1 more source

Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati   +10 more
wiley   +1 more source

A Model for Programmability and Virtuality in Dynamical Neural Networks

open access: yes, 2009
In this dissertation a fixed-weight architecture for Continuous Time Recurrent Neural Networks (CTRNNs) is proposed in order to give an account for biological phenomena, controlled by neuronal activity, in which changes of behavior occur so fast that ...
Donnarumma, Francesco
core  

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown   +6 more
wiley   +1 more source

Organizational regularities in recurrent neural networks

open access: yesFrontiers in Complex Systems
Previous work has shown that the dynamical regime of Recurrent Neural Networks (RNNs)—ranging from oscillatory to chaotic and fixed point behavior—can be controlled by the global distribution of weights in connection matrices with statistically ...
Claus Metzner   +3 more
doaj   +1 more source

Interactive Evolving Recurrent Neural Networks Are Super-Turing Universal

open access: yes, 2014
Understanding the dynamical and computational capabilities of neural models represents an issue of central importance. In this context, recent results show that interactive evolving recurrent neural networks are super-Turing, irrespective of whether ...
Jérémie Cabessa   +3 more
core   +1 more source

Home - About - Disclaimer - Privacy