Abstract: A recently proposed fast image alignment algorithm is the inverse compositional algorithm based on LucasKanade. In this paper, we present an overview of different brightness and gradient constraints used with the inverse compositional algorithm. We also propose an efficient and robust data constraint for the estimation of global motion from image sequences. The constraint combines bri...

Metaheuristic techniques have been recently used to counter the problems like slow convergence to global minima and network stagnancy in backpropagation neural network (BPNN) algorithm. Previously, a meta-heuristic search algorithm called Bat was proposed to train BPNN to achieve fast convergence in the neural network. Although, Bat-BP algorithm achieved fast convergence but it had a problem of...

X-ray imaging is commonly used in clinical routine. In radiotherapy, spatial information is extracted from X-ray images to correctly position patients before treatment. Similarly, orthopedic surgeons assess the positioning and migration of implants after Total Hip Replacement (THR) with X-ray images. However, the projective nature of X-ray imaging hinders the reliable extraction of rigid struct...

In this study a hybrid differential evolution-back-propagation algorithm to optimize the weights of feedforward neural network is proposed.The hybrid algorithm can achieve faster convergence speed with higher accuracy. The proposed hybrid algorithm combining differential evolution (DE) and back-propagation (BP) algorithm is referred to as DE-BP algorithm to train the weights of the feed-forward...

The Three Step Bacterial Memetic Algorithm is proposed. This new version of the Bacterial Memetic Algorithm with Modified Operator Execution Order (BMAM) is applied in a practical problem, namely is proposed as the Fuzzy Neural Networks (FNN) training algorithm. This paper strove after the improvement of the function approximation capability of the FNNs by applying a combination of evolutionary...

A nonlinear conjugate gradient algorithm which is a modification of the Dai and Yuan [Y.H. Dai and Y, Yuan, A nonlinear conjugate gradient method with a strong global convergence property, SIAM J. Optim., 10 (1999), pp.177-182.] conjugate gradient algorithm satisfying a parametrized sufficient descent condition with a parameter k δ is proposed. The parameter k δ is computed by means of the conj...

A direct search algorithm is proposed for minimizing an arbitrary real valued function. The algorithm uses a new function transformation and three simplex-based operations. The function transformation provides global exploration features, while the simplex-based operations guarantees the termination of the algorithm and provides global convergence to a stationary point if the cost function is d...

Combining the techniques of the working set identification and generalized gradient projection, we present a new generalized gradient projection algorithm for minimax optimization problems with inequality constraints. In this paper, we propose a new optimal identification function, from which we provide a new working set. At each iteration, the improved search direction is generated by only one...

The paper presents a global chassis control (GCC) optimization approach using a gradient-based optimal control algorithm. The goal is to find optimal actions of various actuators such as active steering and active differential, which ensure satisfying the optimization criterion (e.g. trajectory following error minimization) subject to different equality and inequality constraints on state and c...