A numerical scheme for the analytic continuation of radiation patterns of the azimuthal coordinate θ into the whole space over the complex plane is given. The scattering data given over the real space [0, 2π] are extended into the complex plane by using the recurrence formulas. An example shows the validity of mathematically exact evaluation for the scattering from polygonal cylinders.

A systematic method for locating and computing branches of connecting orbits developed by the authors is outlined. The method is applied to the sine–Gordon and Hodgkin–Huxley equations.

Pitch frequency is a basic characteristic of human voice, and pitch extraction is one of the most important studies for speech recognition. This paper describes a simple but effective technique to obtain correct pitch frequency from candidates (pitch candidates) extracted by the short-range autocorrelation function. The correction is performed by a neural network in consideration of the time coutinuation that is realized by referring to pitch candidates at previous frames. Since the neural network is trained by the back-propagation algorithm with training data, it adapts to any speaker and obtains good correction without sensitive adjustment and tuning. The pitch extraction was performed for 3 male and 3 female announcers, and the proposed method improves the percentage of correct pitch from 58.65% to 89.19%.

Algorithms for computing channel capacity have been proposed by many researchers. Recently, one of the authors proposed an efficient algorithm using Newton's method. Since this algorithm has local quadratic convergence, it is advantageous when we want to obtain a numerical solution with high accuracy. In this letter, it is shown that this algorithm can be extended to the algorithm for computing the constrained capacity, i.e., the capacity of discrete memoryless channels with linear constraints. The global convergence of the extended algorithm is proved, and its effectiveness is verified by numerical examples.

This paper presents an efficient algorithm for computing the capacity of discrete memoryless channels. The algorithm uses Newton's method which is known to be quadratically convergent. First, a system of nonlinear equations termed Kuhn-Tucker equations is formulated, which has the capacity as a solution. Then Newton's method is applied to the Kuhn-Tucker equations. Since Newton's method does not guarantee global convergence, a continuation method is also introduced. It is shown that the continuation method works well and the convergence of the Newton algorithm is guaranteed. By numerical examples, effectiveness of the algorithm is verified. Since the proposed algorithm has local quadratic convergence, it is advantageous when we want to obtain a numerical solution with high accuracy.