The Design and Complexity of Exact Multilayered Perceptrons

Delamination of Two-Dimensional Functionally Graded Multilayered Non-Linear Elastic Beam - an Analytical Approach

Delamination fracture of a two-dimensional functionally graded multilayered four-point bending beam that exhibits non-linear behaviour of the material is analyzed. The fracture is studied analytically in terms of the strain energy release rate. The beam under consideration has an arbitrary number of layers. Each layer has individual thickness and material properties. A delamination crack is loc...

LETTER Communicated by Sun - Ichi AmariOn \ Natural " Learning and Pruning in Multilayered PerceptronsTom

Several studies have shown that natural gradient descent for on-line learning is much more eecient than standard gradient descent. In this paper, we derive natural gradients in a slightly diierent manner and discuss implications for batch-mode learning and pruning, linking them to existing algorithms such as Levenberg-Marquardt optimization and optimal brain surgeon. The Fisher matrix plays an ...

Control of complexity in learning with perturbed inputs

This paper considers the problem of function approximation from scattered data when using multilayered perceptrons. We present a new algorithm based on the principle of Inputs Perturbation, improving the generalization performances of backpropagation. In this algorithm, a new parameter is introduced in order to allow a control of the complexity of the t. This parameter balances the bias versus ...

Prediction Model for CNC Turning on AISI316 with Single and Multilayered Cutting tool Using Box Behnken Design (RESEARCH NOTE)

Austenitic stainless steels (AISI316) are used for many commercial and industrial applications for their excellent corrosive resistance. AISI316 is generally difficult to machine material due to their high strength and high work hardening tendency. Tool wear (TW) and surface roughness (SR) are broadly considered the most challenging phases causing poor quality in machining. Optimization of cutt...

Probabilistic decision trees ans multilayered perceptrons