This paper presents an analysis on energy consumption and energy efficiency of a hexapod robot during its turning motion over flat terrain. The energy consumption model has been derived for statically stable wave-turning gaits by considering a minimization of dissipating energy for optimal foot force distribution. Two approaches, such as minimization of norm of feet forces and minimization of n...

We examine the NFA minimization problem in terms of atomic NFA’s, that is, NFA’s in which the right language of every state is a union of atoms, where the atoms of a regular language are non-empty intersections of complemented and uncomplemented left quotients of the language. We characterize all reduced atomic NFA’s of a given language, that is, those NFA’s that have no equivalent states. Usin...

In this paper we study general Schatten-p quasi-norm (SPQN) regularized matrix minimization problems. In particular, we first introduce a class of first-order stationary points for them, and show that the first-order stationary points introduced in [11] for an SPQN regularized vector minimization problem are equivalent to those of an SPQN regularized matrix minimization reformulation. We also s...

a model capable of predicting the minimum content of aflatoxin m1 (afm1) in iranian while brine cheese has been developed using a chemometric approach to determine the optimum processing conditions. renneting temperature, cut size, stirring time, press time, curd size and saturated brine ph were all regarded as process variables. three-dimensional response surface and contour plots were drawn. ...

A modified Newton method for unconstrained minimization is presented and analyzed. The modification is based upon the model trust region approach. This report contains a thorough analysis of the locally constrained quadratic minimizations that arise as subproblems in the modified Newton iteration. Several promising alternatives are presented for solving these subproblems in ways that overcome c...

In this paper, we present a simple analysis of fast rates with high probability of empirical minimization for stochastic composite optimization over a finite-dimensional bounded convex set with exponentially concave loss functions and an arbitrary convex regularization. To the best of our knowledge, this result is the first of its kind. As a byproduct, we can directly obtain the fast rate with ...

Matrix rank minimization problem is widely applicable in many fields such as control, signal processing and system identification. However, the problem is in general NP-hard, and it is computationally hard to solve directly in practice. In this paper, we provide a new kind of approximation functions for the rank of matrix, and the corresponding approximation problems can be used to approximate ...

In this paper, a class of minimization problems, labeled by an index 0 < h < 1, is considered. Each minimization problem is for a freeenergy, motivated by the magnetics in 3D-ferromagnetic thin film, and in the context, the index h denotes the thickness of the observing film. The Main Theorem consists of two themes, which are concerned with the study of the solvability (existence of minimizers)...

Alternating minimization has emerged as a popular heuristic for large-scale machine learning problems involving low-rank matrices. However, there have been few (if any) theoretical guarantees on its performance. In this work, we investigate the natural alternating minimization algorithm for the popular matrix sensing problem first formulated in [RFP07]; this problem asks for the recovery of an ...

Logic synthesis is a novel architectural concept used for converting a high level description of logic circuit into optimized gate level description. The method ranges from transforming a RTL description to producing an optimized netlist. Logic minimization plays an important role in optimization of logic synthesis. This optimization is done through the function minimization through different e...