Retrieving information from remotely sensed data is an important task. In the present work, data of L band microwave radiometer has been used to collect the brightness temperature over bare and vegetated fields in two polarizations at different moisture levels. Artificial neural network (ANN) trained with Levenberg-Marquardt algorithm has been used to determine soil moisture from brightness tem...

We present a deterministic and direct method inspired by the ideas of the Power Series Method applied to solve a chemical kinetics inverse problem. We use a power series as a trial solution approximation, and the data is used as initial condition and boundary value condition to solve the coupled differential equation of chemical kinetics and to obtain the rate constant parameters. The approach ...

This paper investigates the use of three back-propagation training algorithms, Levenberg-Marquardt, conjugate gradient and resilient back-propagation, for the two case studies, stream-flow forecasting and determination of lateral stress in cohesionless soils. Several neural network (NN) algorithms have been reported in the literature. They include various representations and architectures and t...

Prediction of the gas holdup and pressure drop in a horizontal pipe for gas-non-Newtonian liquid flow using Artificial Neural Networks (ANN) methodology have been reported in this paper from the data acquired from our earlier experiment. The ANN prediction is done using Multilayer Perceptrons (MLP) trained with three different algorithms, namely: Backpropagation (BP), Scaled Conjugate gradient ...

In this work, we describe a method for the classification of respiratory states based on four significant features using Artificial neural network (ANN). These features are extracted from the respiratory signals using modified threshold algorithm were fed as input parameters to the ANN for classification. A gradient based search algorithms are usually being used in ANN to find a set of suitable...

For managing data in a smart card’s limited memory, containing medical and biometric images, images compression is resorted to. For image retrieval, it is necessary that the classification algorithm be efficient to search and locate the image in a compressed domain. This study proposes a novel training algorithm for Multi-Layer Perceptron Neural Network (MLP-NN) to classify compressed images. M...

This paper describes a method of dogleg trust-region steps, or restricted Levenberg-Marquardt steps, based on a projection process onto the Krylov subspaces for neural networks nonlinear least squares problems. In particular, the linear conjugate gradient (CG) method works as the inner iterative algorithm for solving the linearized Gauss-Newton normal equation, whereas the outer nonlinear algor...

RNNs have local feedback loops within the network which allows them to shop earlier accessible patterns. This network can be educated with gradient descent back propagation and optimization technique such as second-order methods; conjugate gradient, quasi-Newton, Levenberg-Marquardt have also been used for networks training [14, 15]. But still this algorithm is not definite to find the global m...

Unmanned Aircraft Systems (UAS) have been widely applied for reconnaissance and surveillance by exploiting the information collected from the digital imaging payload. However, the data analysis of UAS videos is frequently limited by motion blur; the frame-to-frame movement induced by aircraft roll, wind gusts, and less than ideal atmospheric conditions; and the noise inherent within the image s...