Y. Kuroe

发表

A solution to the common Lyapunov function problem for continuous-time systems

Yasuaki Kuroe, Yoshihiro Mori, T. Mori, 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

Comments on "On the robust Popov criterion for interval Lur"e systems

H. Kokame, T. Mori, Y. Kuroe, 1995, IEEE Trans. Autom. Control..

Optimality-Preserving Interval Parameters in SI Regulator Systems

H. Kokame, T. Mori, Y. Kuroe, 1996 .

SICE Annual Conference Steering Committee

Kazuo Kyuma, Yasuaki Kuroe, Mitsuji Sampei, 2007 .

A synthesis method of gene regulatory networks having cyclic expression pattern sequences and its evaluation

Y. Mori, Y. Kuroe, 2012, 2012 12th International Conference on Control, Automation and Systems.

Controller design method of gene networks based on gene expression patterns by network learning

Y. Mori, Y. Kuroe, 2009, 2009 ICCAS-SICE.

Linearizing Control of Synchronous Motors through Decoupling of d-q Axes and its Application to Design of Optimal Speed-Servo Systems

Kazuo Okamura, Yasuaki Kuroe, Toru Maruhashi, 1989 .

Applications of Clifford’s Geometric Algebra

T. Nitta, Y. Kuroe, E. Hitzer, 2013, Advances in Applied Clifford Algebras.

Analysis Method of Period Sensitivities for Rhythm Phenomena

Y. Mori, Y. Kuroe, 2022, 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Learning Method of Recurrent Spiking Neural Networks to Realize Various Firing Patterns and Its Application

Yutaka Maeda, Hitoshi Iima, Yasuaki Kuroe, 2020, Transactions of the Society of Instrument and Control Engineers.

Estimation of Flow Velocity Vector Fields Using Neural Networks

Yasuaki Kuroe, Ichiro Kimura, Akikazu Kaga, 1998 .

QE Approach to Common Lyapunov Function Problem

Yasuaki Kuroe, Yoshihiro Mori, Takehiro Mori, 2003 .

Learning methods of recurrent Spiking Neural Networks based on adjoint equations approach

Yasuaki Kuroe, Tomokazu Ueyama, Y. Kuroe, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Learning Methods of Recurrent Spiking Neural Networks

Yasuaki Kuroe, Takehiro Mori, Kukan Selvaratnam, 2000 .

Decoupling control of robot manipulators by using variable-structure disturbance observer

Hsin-Nan Lin, Yasuaki Kuroe, Y. Kuroe, 1995, Proceedings of IECON '95 - 21st Annual Conference on IEEE Industrial Electronics.

Models of clifford recurrent neural networks and their dynamics

Yasuaki Kuroe, Y. Kuroe, 2011, The 2011 International Joint Conference on Neural Networks.

2 types of complex-valued Hopfield networks and the application to a traffic signal control

K. Sakakibara, I. Nishikawa, Y. Kuroe, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

A Data-Assimilation Based Method for Equilibrium Reconstruction of Magnetic Fusion Plasma and its Application to Reversed Field Pinch

Yasuaki Kuroe, Akio Sanpei, Sadao Masamune, 2021, IEEE Access.

A computer-aided design method of stabilizing controllers for chaotic systems — External force control

Yasuaki Kuroe, Y. Kuroe, 2015, 2015 10th Asian Control Conference (ASCC).

Computer-aided design method of stabilizing controllers for chaotic systems

Yasuaki Kuroe, Y. Kuroe, 2012, 2012 IEEE International Symposium on Intelligent Control.

A Design Method of Stabilizing Controllers for Chaotic Systems

Y. Kuroe, 2012 .

Applications of Clifford’s Geometric Algebra

Yasuaki Kuroe, Eckhard Hitzer, Tohru Nitta, 2013, Advances in Applied Clifford Algebras.

Relations between Common Quadratic Lyapunov Functions and Common Infinity-Norm Lyapunov Functions

Yasuaki Kuroe, Yoshihiro Mori, Takehiro Mori, 2004 .

Some new subclasses of systems having a common quadratic Lyapunov function and comparison of known subclasses

Y. Mori, Y. Kuroe, T. Mori, 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

Relationships among Known Subclasses of Systems that Havea Common Lyapunov Function

T. Mori, Y. Mori, Y. Kuroe, 2001 .

Models of hopfield-type quaternion neural networks and their energy functions

Yasuaki Kuroe, Mitsuo Yoshida, Takehiro Mori, 2005, Int. J. Neural Syst..

A method of oscillatory trajectory generation using recurrent hybrid neural networks

Y. Kuroe, K. Miura, Y. Kuroe, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Particle Swarm Optimization with Enhanced Autonomous Search Ability of Each Particle

Yasuaki Kuroe, Hitoshi Iima, H. Iima, 2008 .

Swarm reinforcement learning algorithms based on Sarsa method

Y. Kuroe, H. Iima, H. Iima, 2008, 2008 SICE Annual Conference.

Swarm Reinforcement Learning Algorithm Based on Exchanging Information among Agents

Yasuaki Kuroe, Hitoshi Iima, H. Iima, 2006 .

Models of complex-valued dynamic associative memories and analysis of their dynamics - Analytic and non-analytic activation functions -

Yasuaki Kuroe, Yuriko Taniguchi, Y. Kuroe, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Models of Orthogonal Type Complex-Valued Dynamic Associative Memories and Their Performance Comparison

Yasuaki Kuroe, Yuriko Taniguchi, Y. Kuroe, 2007, ICANN.

Models of Self-correlation Type Complex-Valued Associative Memories and Their Dynamics

Yasuaki Kuroe, Yuriko Taniguchi, Y. Kuroe, 2005, ICANN.

APPLICATION OF NEURAL NETWORKS TO QUANTITATIVE FLOW VISUALIZATION

Yasuaki Kuroe, Ichiro Kimura, Mamoru Ozawa, 1993 .

Analysis of hybrid feedback systems with PFM mechanisms

Yasuaki Kuroe, K. Selvaratnam, Takehiro Mori, 1999 .

On Activation Functions for Complex-Valued Neural Networks - Existence of Energy Functions

Yasuaki Kuroe, Mitsuo Yoshida, Takehiro Mori, 2003, ICANN.

Hyperbolic Gradient Operator and Hyperbolic Back-Propagation Learning Algorithms

Yasuaki Kuroe, Tohru Nitta, T. Nitta, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Variable Structure Control of Flexible Robotic Arm

Yasuaki Kuroe, Y. Kuroe, 1993, Robotics, Mechatronics and Manufacturing Systems.

Swarm reinforcement learning methods for problems with continuous state-action space

Yasuaki Kuroe, Hitoshi Iima, Kazuo Emoto, 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

Swarm Reinforcement Learning Method Based on an Actor-Critic Method

Yasuaki Kuroe, Hitoshi Iima, H. Iima, 2010, SEAL.

Models of Hopfield-Type Clifford Neural Networks and Their Energy Functions - Hyperbolic and Dual Valued Networks -

Yasuaki Kuroe, Hitoshi Iima, Shinpei Tanigawa, 2011, ICONIP.

Phase dynamics of complex-valued neural networks and its application to traffic signal control

Yasuaki Kuroe, Kazutoshi Sakakibara, Ikuko Nishikawa, 2005, Int. J. Neural Syst..

Synthesis of spiking neural oscillators

Yasuaki Kuroe, K. Selvaratnam, Takehiro Mori, 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

Computer Aided Method for Analyzing Hybrid Continuous/Discrete Time Systems and its Application to Parameter Optimization

Y. Kuroe, H. Kusachi, Y. Kuroe, 1990 .

Swarm Reinforcement Learning Algorithm Based on Particle Swarm Optimization Whose Personal Bests Have Lifespans

Yasuaki Kuroe, Hitoshi Iima, H. Iima, 2009, ICONIP.

ESTIMATION. AND CONTROL AND/OR ANALYSIS

Hiromasa Haneda, Yasuaki Kuroe, H. Haneda, 1986 .

A new neural network learning of inverse kinematics of robot manipulator

Y. Kuroe, Y. Nakai, T. Mori, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Swarm reinforcement learning methods improving certainty of learning for a multi-robot formation problem

Yasuaki Kuroe, Hitoshi Iima, H. Iima, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).