A stability theorem for stochastic differential equations with application to storage processes, random walks and optimal stochastic control problems

AbstractFor a sequence of stochastic differential equations of type Xn(t)=Xn(0)+ʃt0aN(S, XN(S−)) dAn(S)+ʃt0ʃR\{0}cn(S,Xn(S−))dn(S,Xn(S−),x)Ñn(ds dx)+Bn(t), a stability theorem is presented under an appropriate convergence mode of coefficients an, cn, dn, driving processes An, Bn and martingale measures Ñn. Applications to limit theorems for storage processes, random walks and optimal control problems are shown

〈Reports on the Twenty-second Annual Meeting of the Tsukuba English Linguistic Society〉Dissimilation of Sonorants in English

Dissimilation is a sound change by which two segments of certain similarity become more distinct in properties such as place and manner of articulation. A few selected examples are as follows: ..

Toward a Unified Analysis of Honorification Phenomena in Japanese Existential and Possessive Constructions : Is the Subject of Possessive Construction Really the Dative NP?

This paper is concerned with honorification phenomena in Japanese existential and possessive contructions. In Japanese, the subject honorific form of a predicate is preferred to the plain one when the subject of a sentence refers to a person to whom a speaker should pay defernce.

Changes in Electroencephalography and Cardiac Autonomic Function During Craft Activities: Experimental Evidence for the Effectiveness of Occupational Therapy

Occupational therapy often uses craft activities as therapeutic tools, but their therapeutic effectiveness has not yet been adequately demonstrated. The aim of this study was to examine changes in frontal midline theta rhythm (Fmθ) and autonomic nervous responses during craft activities, and to explore the physiological mechanisms underlying the therapeutic effectiveness of occupational therapy. To achieve this, we employed a simple craft activity as a task to induce Fmθ and performed simultaneous EEG and ECG recordings. For participants in which Fmθ activities were provoked, parasympathetic and sympathetic activities were evaluated during the appearance of Fmθ and rest periods using the Lorenz plot analysis. Both parasympathetic and sympathetic indices increased with the appearance of Fmθ compared to during resting periods. This suggests that a relaxed-concentration state is achieved by concentrating on craft activities. Furthermore, the appearance of Fmθ positively correlated with parasympathetic activity, and theta band activity in the frontal area were associated with sympathetic activity. This suggests that there is a close relationship between cardiac autonomic function and Fmθ activity

Randomized Group-Greedy Method for Large-Scale Sensor Selection Problems

The randomized group-greedy method and its customized method for large-scale sensor selection problems are proposed. The randomized greedy sensor selection algorithm is applied straightforwardly to the group-greedy method, and a customized method is also considered. In the customized method, a part of the compressed sensor candidates is selected using the common greedy method or other low-cost methods. This strategy compensates for the deterioration of the solution due to compressed sensor candidates. The proposed methods are implemented based on the D- and E-optimal design of experiments, and numerical experiments are conducted using randomly generated sensor candidate matrices with potential sensor locations of 10,000--1,000,000. The proposed method can provide better optimization results than those obtained by the original group-greedy method when a similar computational cost is spent as for the original group-greedy method. This is because the group size for the group-greedy method can be increased as a result of the compressed sensor candidates by the randomized algorithm. Similar results were also obtained in the real dataset. The proposed method is effective for the E-optimality criterion, in which the objective function that the optimization by the common greedy method is difficult due to the absence of submodularity of the objective function. The idea of the present method can improve the performance of all optimizations using a greedy algorithm

A FUNDAMENTAL STUDY ON BASEBALL BATTING MOVEMENT FOCUS ON SLAPPING

The purpose of this study is to generate baseball batting style to hit more certainly and to investigate effectiveness it. The idea for new batting referred to bunt and slap hitting used by softball. This new batting style was named A Kourituteki Batting (AKB). 4 male university students participate in this experiment. Subject tried to swing 30 fast balls thrown from pitching machine. 30 trials were divided into 3 groups (right-handed, left-handed, AKB). The result of AKB is higher than left-handed groups. And, the height of loin for AKB is higher than the other groups. This result shows that it may be possible for a using AKB hit a ball more in batter box him always in. This experiment will be useful for considering more developed batting technique in baseball after this

Data-Driven Sensor Selection Method Based on Proximal Optimization for High-Dimensional Data With Correlated Measurement Noise

The present paper proposes a data-driven sensor selection method for a high-dimensional nondynamical system with strongly correlated measurement noise. The proposed method is based on proximal optimization and determines sensor locations by minimizing the trace of the inverse of the Fisher information matrix under a block-sparsity hard constraint. The proposed method can avoid the difficulty of sensor selection with strongly correlated measurement noise, in which the possible sensor locations must be known in advance for calculating the precision matrix for selecting sensor locations. The problem can be efficiently solved by the alternating direction method of multipliers, and the computational complexity of the proposed method is proportional to the number of potential sensor locations when it is used in combination with a low-rank expression of the measurement noise model. The advantage of the proposed method over existing sensor selection methods is demonstrated through experiments using artificial and real datasets