Nonlinear conjugate gradient method is well known in solving large-scale unconstrained optimization problems due to it’s low storage requirement and simple to implement. Research activities on it’s application to handle higher dimensional systems of nonlinear equations are just beginning. This paper presents a Threeterm Conjugate Gradient algorithm for solving Large-Scale systems of nonlinear e...

Abstract. In this paper, the triangulation method, the classic algorithm for Sammon’s projection and the combination of Sammon’s algorithm with the triangulation method are examined for mapping new points in detail. A new realization of the combination of Sammon’s algorithm and the triangulation method is proposed. These algorithms are analyzed and compared in the following respects: visual eva...

The intrinsic cost of polyhedra has lead to research on more tractable sub-classes of linear inequalities. Rather than committing to the precision of such a sub-class, this paper presents a projection algorithm that works directly on any sparse system of inequalities and which sacrifices precision only when necessary. The algorithm is based on a novel combination of the Fourier-Motzkin algorith...

In this paper, we propose an approximate projected consensus algorithm for a network to cooperatively compute the intersection of convex sets. Instead of assuming the exact convex projection proposed in the literature, we allow each node to compute an approximate projection and communicate it to its neighbors. The communication graph is directed and time-varying. Nodes update their states by we...

The least-squares projection procedure appears frequently in mathematics, science, and engineering. It possesses the well-known property that a least-squares approximation (formed via orthogonal projection) to a given data set provides an optimal fit in the chosen norm. The orthogonal projection of the data onto a finite basis is typically approached by the inversion of a Gram matrix involving ...

It is well known that fast affine projection algorithms can produce a good trade-off between convergence speed and computational complexity. Recently, a multichannel fast affine projection algorithm was introduced for active noise control, using a sliding window recursive leastsquares algorithm inside the affine projection algorithm. It was reported that not only can this algorithm provide the ...

We are developed a modified version of affine projection algorithm for acoustic echo cancellation, which has moderate convergence speed and noiserobust characteristics. The proposed algorithm normalizes the update equation to reduce noise effect of affine projection algorithm, by adding the multiplication of estimation error power and projection order to auto-covariance matrix of input signal. ...

Ab8tmctWe examine the representation of signals by the Wavelet 'lhansform Modulus Maxima together with the alternating projection reconstruction algorithm proposed by Mallat. We show that the projection algorithm of Mallat is not minimum distance and not necessarily nonexpansive. Convergence is therefore not guaranteed. We describe an alternative projection operator which is minimum distance an...