Nguyen Thi Hoai Linh
Osaka University
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Nguyen Thi Hoai Linh.
Analysis and Applications | 2014
Ta Viet Ton; Nguyen Thi Hoai Linh; Atsushi Yagi
We first present a new stochastic version of the Cucker-Smale model of the emergent behavior in flocks in which the mutual communication between individuals is affected by random factor. Then, the existence and uniqueness of global solution to this system are verified. We show a result which agrees with natural fact that under the effect of large noise, there is no flocking. In contrast, if noise is small, then flocking may occur. Paper ends with some numerical examples.
Analysis and Applications | 2011
Nguyen Thi Hoai Linh; Ta Viet Ton
In this paper, we consider a stochastic ratio-dependent predator-prey model. We firstly prove the existence, uniqueness and positivity of the solutions. Then, the boundedness of moments of population are studied. Finally, we show the upper-growth rates and exponential death rates of population under some conditions.
european control conference | 2015
Izumi Masubuchi; Takayuki Wada; Toru Asai; Nguyen Thi Hoai Linh; Yuzo Ohta; Yasumasa Fujisaki
The purpose of this paper is to propose a protocol for distributed multi-agent optimization problem to minimize the average of objective functions of the agents in the network with satisfying constraints of each agent. The exact penalty method is applied to distributed optimization via a linear protocol, with employing two step-size parameters for the objective function and the constraint function of each agent. The proposed protocol works only with the decision variables and does not need additional variables such as dual variables. A proof of the convergence of the proposed protocol is provided as well as the boundedness under mild assumptions. The protocol is also illustrated by a numerical example.
asian control conference | 2015
Izumi Masubuchi; Takayuki Wada; Nguyen Thi Hoai Linh; Toru Asai; Yuzo Ohta; Yasumasa Fujisaki
This paper proposes a protocol for a distributed optimization problem in multi-agent networks with equality and inequality constraints. Instead of computing dual optimizations as in previous protocols that can handle constraints, the proposed protocol utilizes additional data of information on past fulfillment of the constraints. Since equality constraints no longer enjoy techniques exploiting strict feasibility of inequality constraints, problems with equality constraints can never be solved by simply extending methods for inequality constraints. To develop a protocol, this paper introduces two diminishing parameters, one of which controls step sizes of decision variables moving to an optimum, while the other specifies the error bound of the equality constraints in each step of iteration. Appropriate choices of these parameters lead to a proof of consensus and convergence of the proposed protocol. A computational example is provided that illustrates the new protocol.
asian control conference | 2015
Nguyen Thi Hoai Linh; Takayuki Wada; Izumi Masubuchi; Toru Asai; Yasumasa Fujisaki
Convergence time is investigated for a gossip algorithm over a connected signed graph, where each edge of the graph has positive or negative sign. The algorithm is an iterative procedure. At each time, (i) two nodes directly connected with an edge are chosen randomly, (ii) they exchange their values according to the sign of the edge, and (iii) they update their values as the average of each nodes value and its received value. It is shown that the values of the algorithm always converge in mean square, where a bipartite consensus or a trivial consensus is achieved. A convergence time is defined as the smallest time such that it takes for the values of the algorithm to get within a given neighborhood of the consensus value with high probability, regardless of initial state. An upper bound of the convergence time is given in terms of a characteristic value of the given graph.
conference on decision and control | 2015
Nguyen Thi Hoai Linh; Takayuki Wada; Izumi Masubuchi; Toru Asai; Yasumasa Fujisaki
This paper investigates two bounded confidence gossip algorithms, one with constant confidence threshold and the other with increasing one, for effective communicating between agents in a network among whom some opinion formation forms. Each agent in the network keeps a real value presenting its opinion about some matter. The opinions of agents will be updated time by time according to an iterative procedure. At each time, (i) two arbitrary agents are chosen randomly, (ii) they exchange their opinions, and (iii) if the distance between the opinions does not exceed some given confidence threshold, they update their opinions as the average of the two. It is shown that the algorithms almost surely drive any initial opinion profile to some opinion profile in which any two opinions either are the same or differ more than the confidence threshold. Moreover, the second algorithm can help achieving a prescribed number of different opinions on the convergence opinion profiles.
arXiv: Dynamical Systems | 2015
Nguyen Thi Hoai Linh; Ta Hong Quang; Ta Viet Ton
arXiv: Probability | 2015
Ta Viet Ton; Nguyen Thi Hoai Linh; Atsushi Yagi
arXiv: Probability | 2015
Nguyen Thi Hoai Linh; Ta Viet Ton; Atsushi Yagi
arXiv: Dynamical Systems | 2015
Nguyen Thi Hoai Linh; Ta Hong Quang; Ta Viet Ton