C(⋅) is the controlled gate (see Definition 2.2.5), and FT† is the inverse quantum Fourier transform FT and can be obtained by reversing the circuit of FT given in the proof of Proposition 2.3.2. Obviously,
With this notation, the position of all of the components and placement is described by a 2N-dimensional vector, (9.12)p→=(x1,…,xi,…,xN,y1,…yi,…,yN)T. A quadratic cost function to minimize wirelength is a primary objective for placement. The Euclidean distance among pairs of ...
COSI leverages probability density functions created from Latin hypercube sampling, ensuring even solution space coverage to improve the stability of the segmentation model. GS widens the exploration scope to combat stagnation during iterations and improve segmentation efficiency. ADN refines convergence ...
Then the convergence of the MSFLA is deeply analyzed and proved theoretically by a new dynamic equation formed by Z-transform. Finally, we have compared the solution of the 7 benchmark functions with the original SFLA, other improved SFLAs, genetic algorithm, PSO, artificial bee colony ...
Multi-threshold image segmentation methods are favored for their computational simplicity and operational efficiency. Existing threshold selection techniques in multi-threshold image segmentation, such as Kapur based on exhaustive enumeration, often hamper efficiency and accuracy. The whale optimization algorithm...
xx xx xxxx A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise Seth W. Egger 1,2 & Mehrdad Jazayeri 1,2 Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. ...
In this paper, we present a detailed analysis on the performance degradation of inverse synthetic aperture radar (ISAR) imagery with the polar format algorithm (PFA) due to the inaccurate rotation center. And a novel algorithm is developed to estimate th
Floor to double and output: double floor_to_double(const K::FT& x) { double a = floor(CGAL::to_double(x)); while (a > x) a -= 1; while (a+1 <= x) a += 1; return a; } double ceil_to_double(const K::FT& x){ double a = ceil(CGAL::to_double(x)); while (a ...
This method aims at using the Lagrangian formulation to iteratively solve quadratic sub-problems. Asadollahi et al. (2014) implemented SQP for the production optimization of the Brugge model and compared it to Hooke-Jeeves direct search (HJDS), the Nelder-Mead (NM) method, and the generalized ...
In this paper we have studied the optimum correction of the absolute value equation through making minimal changes in the coefficient matrix and the right-hand side using the l(2) norm. Solving this problem is equal to solving a nonconvex and fractional quadratic problem. To solve this problem...