AIMC Topic: Neural Networks, Computer

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Application of neural networks with novel independent component analysis methodologies to a Prussian blue modified glassy carbon electrode array.

Talanta
Sodium potassium absorption ratio (SPAR) is an important measure of agricultural water quality, wherein four exchangeable cations (K(+), Na(+), Ca(2+) and Mg(2+)) should be simultaneously determined. An ISE-array is suitable for this application beca...

Adaptive NN Control of a Class of Nonlinear Systems With Asymmetric Saturation Actuators.

IEEE transactions on neural networks and learning systems
In this note, adaptive neural network (NN) control is investigated for a class of uncertain nonlinear systems with asymmetric saturation actuators and external disturbances. To handle the effect of nonsmooth asymmetric saturation nonlinearity, a Gaus...

A Neurodynamic Optimization Method for Recovery of Compressive Sensed Signals With Globally Converged Solution Approximating to l0 Minimization.

IEEE transactions on neural networks and learning systems
Finding the optimal solution to the constrained l0 -norm minimization problems in the recovery of compressive sensed signals is an NP-hard problem and it usually requires intractable combinatorial searching operations for getting the global optimal s...

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous metho...

Discrete-Time Zhang Neural Network for Online Time-Varying Nonlinear Optimization With Application to Manipulator Motion Generation.

IEEE transactions on neural networks and learning systems
In this brief, a discrete-time Zhang neural network (DTZNN) model is first proposed, developed, and investigated for online time-varying nonlinear optimization (OTVNO). Then, Newton iteration is shown to be derived from the proposed DTZNN model. In a...

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

IEEE transactions on neural networks and learning systems
This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by ne...

A hierarchical model of goal directed navigation selects trajectories in a visual environment.

Neurobiology of learning and memory
We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model's fle...

Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments.

Food chemistry
Bananas (cv. Musa nana and Musa cavendishii) fresh and dried by hot air at 50 and 70°C and lyophilisation were analysed for phenolic contents and antioxidant activity. All samples were subject to six extractions (three with methanol followed by three...

Further result on guaranteed H∞ performance state estimation of delayed static neural networks.

IEEE transactions on neural networks and learning systems
This brief considers the guaranteed H∞ performance state estimation problem of delayed static neural networks. An Arcak-type state estimator, which is more general than the widely adopted Luenberger-type one, is chosen to tackle this issue. A delay-d...

Is extreme learning machine feasible? A theoretical assessment (part II).

IEEE transactions on neural networks and learning systems
An extreme learning machine (ELM) can be regarded as a two-stage feed-forward neural network (FNN) learning system that randomly assigns the connections with and within hidden neurons in the first stage and tunes the connections with output neurons i...