EuDML | Browse

Page 1

Displaying 1 – 5 of 5

La docencia de la bioestadística: un cambio de perspectiva.

Francesc Oliva (1996)

Qüestiió

Hace apenas seis años, aparecieron dos números de la revista Estadística Española dedicados a la docencia de la estadística. Releyendo el artículo del profesor C. M. Cuadras y los amplios comentarios de un buen número de profesores del área sobre la docencia de la bioestadística en España, he tenido la impresión de que, a pesar de mantener su validez en líneas generales, la perspectiva ha cambiado radicalmente. En el cambio han intervenido, a mi parecer, dos hechos fundamentales: la irrupción de...

Laplace Adomian decomposition method for solving a fish farm model

M. Sambath, K. Balachandran (2016)

Nonautonomous Dynamical Systems

In this work, a combined form of the Laplace transform method and the Adomian decomposition method is implemented to give an approximate solution of nonlinear systems of differential equations such as fish farm model with three components nutrient, fish and mussel. The technique is described and illustrated with a numerical example.

Large-time dynamics of discrete-time neural networks with McCulloch-Pitts nonlinearity.

Dai, Binxiang, Huang, Lihong, Qian, Xiangzhen (2003)

Electronic Journal of Differential Equations (EJDE) [electronic only]

Limit theorems for discrete-time metapopulation models.

Buckley, F.M., Pollett, P.K. (2010)

Probability Surveys [electronic only]

Local stability conditions for discrete-time cascade locally recurrent neural networks

Krzysztof Patan (2010)

International Journal of Applied Mathematics and Computer Science

The paper deals with a specific kind of discrete-time recurrent neural network designed with dynamic neuron models. Dynamics are reproduced within each single neuron, hence the network considered is a locally recurrent globally feedforward. A crucial problem with neural networks of the dynamic type is stability as well as stabilization in learning problems. The paper formulates local stability conditions for the analysed class of neural networks using Lyapunov's first method. Moreover, a stabilization...