In this paper, we described and developed a framework for Multilayer Perceptron (MLP) to work on low level image processing, where MLP will be used to perform image super-resolution. Meanwhile, MLP are trained with different types of images from various categories, hence analyse the behaviour and performance of the neural network. The tests are carried out using qualitative test, in which Mean ...

The present paper deals with the continuous work of extending multi-dimensional limiting process (MLP) onto correction procedure via reconstruction (CPR). MLP, which has been originally developed in finite volume method (FVM), provides an accurate, robust and efficient oscillation-control mechanism in multiple dimensions for linear reconstruction. Recently, MLP has been extended into higher-ord...

The discrimination powers of Multilayer perceptron (MLP) and Learning Vector Quantisation (LVQ) networks are compared for overlapping Gaussian distributions. It is shown, both analytically and with Monte Carlo studies, that the MLP network handles high dimensional problems in a more eecient way than LVQ. This is mainly due to the sigmoidal form of the MLP transfer function, but also to the the ...

در این مقاله یک مدل ریاضی برای مسئله سیستم تولیدی همکارانه ساخت بر اساس سفارش با رعایت انصاف تخصیص بار‌های تولید طراحی شده است. اهداف اصلی مدل، کمینه‌سازی هزینه‌‌های کل و حداکثر استفاده از منابع به‌منظور عادلانه شرایط عدم­قطعیت کنترل پارامتر‌های غیرقطعی روش برنامه‌ریزی فازی ‌شده نتایج نشان می‌دهد افزایش نرخ عدم‌قطعیت، می­یابد. ازآنجاکه ظرفیت کارخانه‌ها ثابت است، مقدار تقاضا، هر کارخانه نیز می­ی...

This paper presents a new derivation of Akcasu’s Modified Levermore-Pomraning (MLP) model for estimating the ensemble-averaged angular flux for particle transport problems in 1-D geometrically random media. The significant new feature of the MLP equations is that, unlike the earlier Levermore-Pomraning (LP) model, the MLP equations are exact for certain classes of problems with scattering.

Abstract A class of recurrent neural networks is developed to solve nonlinear equations, which are approximated by a multilayer perceptron (MLP). The recurrent network includes a linear Hopfield network (LHN) and the MLP as building blocks. This network inverts the original MLP using constrained linear optimization and Newton’s method for nonlinear systems. The solution of a nonlinear equation ...

Purpose We further optimized and evaluated the safety of the magnetic levator prosthesis (MLP) for temporary management of severe blepharoptosis, and compared efficacy and comfort against the ptosis crutch. Methods The interpalpebral fissure (IPF) of participants (n = 12) with ptosis was measured during attempted eyelid opening, volitional closing, and spontaneous closing with no device, ptos...

The capabilities of Locally Recurrent Neural Networks (LRNNs) in performing on-line Signal Processing (SP) tasks are well known [1,3,5,6,10,11,14,15]. In particular one of the most popular architecture is the Multi Layer Perceptron (MLP) with linear IIR temporal filter synapses (IIR-MLP) [3,5,10,11,14,15]. IIR-MLP is theoretically motivated as a non-linear generalization of linear adaptive IIR ...