AIMC Topic: Neural Networks, Computer

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Direct Multitype Cardiac Indices Estimation via Joint Representation and Regression Learning.

IEEE transactions on medical imaging
Cardiac indices estimation is of great importance during identification and diagnosis of cardiac disease in clinical routine. However, estimation of multitype cardiac indices with consistently reliable and high accuracy is still a great challenge due...

Sequence based predictor for discrimination of enhancer and their types by applying general form of Chou's trinucleotide composition.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Enhancers are pivotal DNA elements, which are widely used in eukaryotes for activation of transcription genes. On the basis of enhancer strength, they are further classified into two groups; strong enhancers and weak enhanc...

DeepPPI: Boosting Prediction of Protein-Protein Interactions with Deep Neural Networks.

Journal of chemical information and modeling
The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many proteins variants statistically associated with human disease, nearly all such variants have unknown mechanisms, for example,...

Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network.

PloS one
Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes informa...

Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper investigates master-slave exponential synchronization for a class of complex-valued memristor-based neural networks with time-varying delays via discontinuous impulsive control. Firstly, the master and slave complex-valued memristor-based ...

Hybrid impulsive and switching Hopfield neural networks with state-dependent impulses.

Neural networks : the official journal of the International Neural Network Society
We discuss the global stability of switching Hopfield neural networks (HNN) with state-dependent impulses using B-equivalence method. Under certain conditions, we show that the state-dependent impulsive switching systems can be reduced to the fixed-t...

Memristor standard cellular neural networks computing in the flux-charge domain.

Neural networks : the official journal of the International Neural Network Society
The paper introduces a class of memristor neural networks (NNs) that are characterized by the following salient features. (a) The processing of signals takes place in the flux-charge domain and is based on the time evolution of memristor charges. The...

A new near-lossless EEG compression method using ANN-based reconstruction technique.

Computers in biology and medicine
Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compression methods utilize fixed transforms such as discrete cosine transform (DCT) and wavelet and usually c...

Prediction of dissolved oxygen concentration in hypoxic river systems using support vector machine: a case study of Wen-Rui Tang River, China.

Environmental science and pollution research international
Accurate quantification of dissolved oxygen (DO) is critically important for managing water resources and controlling pollution. Artificial intelligence (AI) models have been successfully applied for modeling DO content in aquatic ecosystems with lim...

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

eNeuro
Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons w...