This article presents an alternative approach useful for medical practitioners who wish to detect malaria and accurately identify the level of severity. Malaria classifiers are usually based on feed forward neural networks. In this study, the proposed classifier is developed based on the Jordan-Elman neural networks. Its performance is evaluated using a receiver-operating characteristic curve, ...

In this paper, we investigate two different recurrent neural network (RNN) architectures: Elman RNN and recently proposed clockwork RNN [1] for statistical parametric speech synthesis (SPSS). Of late, deep neural networks are being used for SPSS which involve predicting every frame independent of the previous predictions, and hence requires post-processing for ensuring smooth evolution of speec...

As the air-conditioning control system has the nonlinearity, large time delay and time variation and other characteristics.In this paper,we put forward a method of self-adjusting PID algorithm based on the modified Elman neural network, and the output of the network adjust the three parameters of the PID controller online, so that it has the high controlling precision, good dynamic characterist...

In this paper, in order to categorize ORL database face pictures, principle Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) methods by using Elman neural network and Support Vector Machine (SVM) categorization methods are used. Elman network as a recurrent neural network is proposed for modeling storage systems and also it is used for reviewing the effect of using PCA nu...

We present results of experiments with Elman recurrent neural networks (Elman, 1990) trained on a natural language processing task. The task was to learn sequences of word categories in a text derived from a primary school reader. The grammar induced by the network was made explicit by cluster analysis which revealed both the representations formed during learning and enabled the construction o...

Elman network is a class of recurrent neural networks used for function approximation. It has a set of global sigmoid functions at its hidden units. That means that if the operating conditions of a process be identified, are changed the function approximation property of the network is degraded. This is due to the fact that the universes of discourse of the network is covered by global sigmoid ...

Air pollution is a significant risk factor for a number of health conditions including respiratory infections, heart disease like stroke and lung cancer. Further, air pollution exposure is a risk factor correlating with increased total mortality from cardiovascular events and Lung disease such as chronic bronchitis and emphysema. A severe health issue is on the other hand constituted by high le...