Abstract— Image Thresholding is one simplest method of image segmentation, which partitions the image into several objects on the basis of one or more threshold values. Threshold values are the values chosen from the intensity values of the image. In this paper, 8-bit unsigned gray scale images are taken as sample where the intensity values ranges from 0 to 255. Here Kapur's entropy criterion m...

In this paper, humanoid gait generation is formulated as a multi-objective optimization problem with multiconstraint based on probability distribution models. Under this framework, an estimation of distribution algorithm (EDA) based gait optimization approach has been developed to speed up searching in high dimensional coupling space constructed by the permutation of optimization parameters to ...

This paper discusses efficient parameter estimation methods for joint (unconditional) maximum entropy language models such as whole-sentence models. Such models are a sound framework for formalizing arbitrary linguistic knowledge in a consistent manner. It has been shown that general-purpose gradient-based optimization methods are among the most efficient algorithms for estimating parameters of...

Multiple-target tracking (MTT) in the presence of spurious measurements poses difficult computational challenges related to the measurement-to-track data association problem. Different approaches have been proposed to tackle this problem, including various approximations and heuristic optimization tools. The Cross Entropy (CE) and the related Parametric MinxEnt (PME) methods are recent optimiza...

The thermodynamic functions such as enthalpy (H), Gibbs free energy (G) and entropy (S) ofPyrazole was theoretically studied at 5 different temperatures 25, 30, 35, 40 and 45°C by usingGussian o3, software. First, the structural optimization of isolated Pyrazole was done in the gas phaseby appling the Density Functional Theory (B3LYP) level with 3-21G, 6-31G and 6-31+G(d) basissets. Moreover, v...

This work presents PESMOC, Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints, an information-based strategy for the simultaneous optimization of multiple expensive-to-evaluate black-box functions under the presence of several constraints. PESMOC can hence be used to solve a wide range of optimization problems. Iteratively, PESMOC chooses an input location on w...

Partial Transmit Sequence technique is one of the most popular technique for PAPR reduction in OFDM. But in this scheme the complexity for searching the phase factor is increased with increase in number of sub blocks. This paper describes the different types of optimization methods used in PTS scheme, for optimization of phase factor & reducing the searching complexity .Also we can analyze thei...

generally, exponential Lévy models to a finite set of observed option prices. We show that the usual formulations of the inverse problem via non-linear least squares are ill-posed and propose a regularization method based on relative entropy: we reformulate our calibration problem into a problem of finding a risk-neutral exponential Lévy model that reproduces the observed option prices and has ...

Recently, a new algorithm named dynamic group optimization (DGO) has been proposed, which lends itself strongly to exploration and exploitation. Although DGO has demonstrated its efficacy in comparison to other classical optimization algorithms, DGO has two computational drawbacks. The first one is related to the two mutation operators of DGO, where they may decrease the diversity of the popula...