AIMC Topic: Neural Networks, Computer

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Cost-efficient FPGA implementation of basal ganglia and their Parkinsonian analysis.

Neural networks : the official journal of the International Neural Network Society
The basal ganglia (BG) comprise multiple subcortical nuclei, which are responsible for cognition and other functions. Developing a brain-machine interface (BMI) demands a suitable solution for the real-time implementation of a portable BG. In this st...

Multistability and Instability of Neural Networks With Discontinuous Nonmonotonic Piecewise Linear Activation Functions.

IEEE transactions on neural networks and learning systems
In this paper, we discuss the coexistence and dynamical behaviors of multiple equilibrium points for recurrent neural networks with a class of discontinuous nonmonotonic piecewise linear activation functions. It is proved that under some conditions, ...

A novel method for early diagnosis of Alzheimer's disease based on pseudo Zernike moment from structural MRI.

Neuroscience
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common type of dementia among older people. The number of patients with AD will grow rapidly each year and AD is the fifth leading cause of death for those aged 65 and ...

Context-dependent coding and gain control in the auditory system of crickets.

The European journal of neuroscience
Sensory systems process stimuli that greatly vary in intensity and complexity. To maintain efficient information transmission, neural systems need to adjust their properties to these different sensory contexts, yielding adaptive or stimulus-dependent...

Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle.

IEEE transactions on neural networks and learning systems
This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an...

Broiler responses to digestible threonine at different ages: a neural networks approach.

Journal of animal physiology and animal nutrition
Three experiments were conducted with broiler chickens to evaluate the effects of digestible threonine (DThr) and crude protein (CP) on their performance at three different phases of age: 1-14, 15-28 and 29-42 days. The measured traits included the f...

Novel conditions on exponential stability of a class of delayed neural networks with state-dependent switching.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the global exponential stability on a class of delayed neural networks with state-dependent switching. Under the novel conditions, some sufficient criteria ensuring exponential stability of the proposed system are obtaine...

Pattern recognition for cache management in distributed medical imaging environments.

International journal of computer assisted radiology and surgery
PURPOSE: Traditionally, medical imaging repositories have been supported by indoor infrastructures with huge operational costs. This paradigm is changing thanks to cloud outsourcing which not only brings technological advantages but also facilitates ...

New Results on Passivity Analysis of Stochastic Neural Networks with Time-Varying Delay and Leakage Delay.

Computational intelligence and neuroscience
The passivity problem for a class of stochastic neural networks systems (SNNs) with varying delay and leakage delay has been further studied in this paper. By constructing a more effective Lyapunov functional, employing the free-weighting matrix appr...

A novel multivariate performance optimization method based on sparse coding and hyper-predictor learning.

Neural networks : the official journal of the International Neural Network Society
In this paper, we investigate the problem of optimization of multivariate performance measures, and propose a novel algorithm for it. Different from traditional machine learning methods which optimize simple loss functions to learn prediction functio...