In this paper, we propose a multi-branch neural network architecture named Coupled Modular Neural Network (CMNN). A CMNN is consisting of ? closely coupled sub-networks, where termed as the branching factor in paper. We call whole super-graph and each sub-network sub-graph. Each sub-graph stand-alone shares common block with other sub-graphs. To effectively leverage simple but easy-to-implement...

This research is on presenting a new approach for cardiac arrhythmia disease classification. The proposed method uses Modular neural network (MNN) model to classify arrhythmia into normal and abnormal classes. We have performed experiments on UCI Arrhythmia data set [8]. Missing attribute values of this data set are replaced by closest column value of the concern class. We have constructed neur...

This paper proposes the Mesh Neural Network (MNN), a novel architecture which allows neurons to be connected in any topology, efficiently route information. In MNNs, information is propagated between throughout state transition function. State and error gradients are then directly computed from updates without backward computation. The MNN propagation schema formalized derived tensor algebra. p...

Morphological Neural Networks (MNN) have been proposed as associative memories (with its two cases: autoassociative and heteroassociative). In this paper we are involved with Heteroassociative MNN (HMNN). We propose their use for selflocalization in a vision-based navigation framework for mobile robots. HMNN can be trained in a single computation step. Their storage capacity bound is the dimens...

The values of electronic components are always deviated, but the functions of the modern circuits are more and more precise, which makes the automatic fault diagnosis of analog circuits very complex and difficult. This paper presents an extension-neural-network-type-1ENN-1based method for fault diagnosis of analog circuits. This proposed method combines the extension theory and neural networks ...

A clique of an undirected graph G (V, E) with a vertex set V and an edge set E is a subset of V such that all pairs of vertices are connected by an edge in E. The maximum clique problem (MCP) is to find a clique of maximum size of the graph G. Figure 1(b) shows a maximum clique of the graph Figure 1(a) with 10 vertices and 21 edges. It is one of the first problems which have been proven to be N...

This paper presents classification and characterization of typical power quality disturbancessag, swell, interruption and harmonics employing S-transform analysis combined with modular neural network. S-transform is used to extract various features of disturbance signal as it has excellent time-frequency resolution characteristics and ability to detect disturbance correctly even in the presence...

The artificial neural networks (ANNs) have been applied to various hydrologic problems recently. This research demonstrates static neural approach by applying Modular feedforward neural network to rainfall-runoff modeling for the upper area of Wardha River in India. The model is developed by processing online data over time using static modular neural network modeling. Methodologies and techniq...

In this paper, we develop a hierarchical classifier (an inverted tree-like structure) consisting of an organized set of "blocks" each of which is actually a module that performs a feature extraction and an associated classification. We build each of such blocks by coupling a Mirroring Neural Network (MNN) with a clustering (algorithm) wherein the functions of the MNN are automatic data reductio...