Appendix A. Determination of the amount of investment This appendix provides the details of section 2.4. Appendix A.1. Bayesian Three-layer Perceptron (i) Perceptron A three-layered perceptron with n factors and h hidden units is used as a basis function for a nonlinear system. That is, with the optimal investment rate y as an explained variable and with the vector of the explanatory variable (...

A multilayer perceptron is a feed forward artificial neural network model that maps sets of input data onto a set of appropriate output. It is a modification of the standard linear perceptron in that it uses three or more layers of neurons (nodes) with nonlinear activation functions and is more powerful than the perceptron in that it can distinguish data that is not linearly separable, or separ...

The performance of on line algorithms for learning dichotomies is studied In on line learn ing the number of examples P is equivalent to the learning time since each example is presented only once The learning curve or generalization error as a function of P depends on the schedule at which the learning rate is lowered For a target that is a perceptron rule the learning curve of the perceptron ...

In this paper we propose and analyze a multilayer perceptron-like model with matrix inputs. We applied the proposed model to the financial time series prediction problem, compared it with the standard multilayer perceptron model, and got fairly good results.

The classical perceptron algorithm is an elementary row-action/relaxation algorithm for solving a homogeneous linear inequality system Ax > 0. A natural condition measure associated with this algorithm is the Euclidean width τ of the cone of feasible solutions, and the iteration complexity of the perceptron algorithm is bounded by 1/τ, see Rosenblatt 1962 [14]. Dunagan and Vempala [4] have deve...

In this paper, simulated annealing guided traingularized encryption using multilayer perceptron generated session key (SATMLP) has been proposed for secured wireless communication. Both sender and receiver station uses identical multilayer perceptron and depending on the final output of the both side multilayer perceptron, weights vector of hidden layer get tuned in both ends. After this tunnin...

This talk surveys applications of space dilation in the perceptron-like algorithms for solving systems of linear inequalities in polynomial time: from the ellipsoid algorithm to the modified perceptron algorithm and the perceptron rescaling algorithm. It also suggests a more general version of the latter algorithm and poses an open problem about the lowest complexity of this approach. Space dil...