A multilayer recurrent neural network is proposed for solving continuous-time algebraic matrix Riccati equations in real time. The proposed recurrent neural network consists of four bidirectionally connected layers. Each layer consists of an array of neurons. The proposed recurrent neural network is shown to be capable of solving algebraic Riccati equations and synthesizing linear-quadratic con...

ÐAesthetically appealing patterns are produced by the dynamical behavior of arti®cial neural networks with randomly chosen connection strengths. These feed-forward networks have a single hidden layer of neurons and a single output, which is fed back to the input to produce a scalar time series that is always bounded and often chaotic. Sample attractors are shown and simple computer code is prov...

recurrent pregnancy loss is usually defined as the loss of two or more consecutive pregnancies before 20 weeks of gestation, which occurs in approximately 5% of reproductive-aged women. it has been suggested that women with thrombophilia have an increased risk of pregnancy loss and other adverse pregnancy outcomes. thrombophilia is an important predisposition to blood clot formation and is cons...

We propose a novel recurrent neural network model, where the hidden state hₜ is obtained by permuting vector elements of previous hₜ₋₁ and adding output learned function β(xₜ) input xₜ at time t. In our prediction given second function, which applied to s(hₜ). The method easy implement, extremely efficient, does not suffer from vanishing nor exploding gradients. an extensive set experiments, sh...

Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The ...

DNA N4-methylcytosine (4mC) and N6-methyladenine (6mA) are significant epigenetic modifications. 4mC is closely related to the restriction modification system, 6mA has a hand in process of various cellular activities. In order further explore their functional mechanisms biological significance, overcome bottleneck narrow coverage traditional experimental methods, it needed propose an efficient ...

In this paper, recurrent neural network is used for path planning in the joint space of the robot with obstacle in the workspace of the robot. To design the neural network, first a performance index has been defined as sum of square of error tracking of final executor. Then, obstacle avoidance scheme is presented based on its space coordinate and its minimum distance between the obstacle and ea...

In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...