A Separation of Electroretinograms for Diabetic Retinopathy. - Yutaka Maeda; Takayuki Akashi; Yakichi Kanata (IEICE Trans. Inf. Syst., 1995)

A learning rule of neural networks via simultaneous perturbation and its hardware implementation. - Yutaka Maeda; Hiroaki Hirano; Yakichi Kanata (Neural Networks, 1995)

Pulse density neural network system using simultaneous perturbation learning rule. - Yutaka Maeda; Atsushi Nakazawa; Yakichi Kanata (ICNN, 1997)

Learning rules for neuro-controller via simultaneous perturbation. - Yutaka Maeda; Rui J. P. de Figueiredo (IEEE Trans. Neural Networks, 1997)

HDL Design of Pulse Density Neural Network Using Simultaneous Perturbation. - Yutaka Maeda; Toshiki Tada; Yakichi Tanaka (ICONIP, 1998)

Interval Density Functions in Conflict Analysis. - Yutaka Maeda; Kazuya Senoo; Hideo Tanaka (RSFDGrC, 1999)

Interval Evaluation by AHP with Rough Set Concept. - Kazutomi Sugihara; Yutaka Maeda; Hideo Tanaka (RSFDGrC, 1999)

FPGA Implementation of a Pulse Density Neural Network Using Simultaneous Perturbation. - Yutaka Maeda; Toshiki Tada (IJCNN (3), 2000)

Real-time control and learning using neuro-controller via simultaneous perturbation for flexible arm system. - Yutaka Maeda (ACC, 2002)

Dual models of interval DEA and its extension to interval data. - Tomoe Entani; Yutaka Maeda; Hideo Tanaka (Eur. J. Oper. Res., 2002)

FPGA implementation of bidirectional associative memory using simultaneous perturbation. - Yutaka Maeda; Masatoshi Wakamura (NNSP, 2003)

FPGA implementation of a pulse density neural network with learning ability using simultaneous perturbation. - Yutaka Maeda; Toshiki Tada (IEEE Trans. Neural Networks, 2003)

Neuro-Controller with Simultaneous Perturbation for Robot Arm - Learning of Kinematics and Dynamics without Jacobian. - Yutaka Maeda; Nobutaka Kitajima; Tsubasa Inagaki; Hidenori Onishi (ANNs, 2004)

Non-additive measures by interval probability functions. - Hideo Tanaka; Kazutomi Sugihara; Yutaka Maeda (Inf. Sci., 2004)

FPGA implementation of pulse coupled oscillator. - Yutaka Maeda; Makito Nakatsuka (IJCNN, 2005)

Bidirectional associative memory with learning capability using simultaneous perturbation. - Yutaka Maeda; Masatoshi Wakamura (Neurocomputing, 2005)

Simultaneous perturbation learning rule for recurrent neural networks and its FPGA implementation. - Yutaka Maeda; Masatoshi Wakamura (IEEE Trans. Neural Networks, 2005)

Simultaneous Perturbation Particle Swarm Optimization. - Yutaka Maeda; Toru Kuratani (IEEE Congress on Evolutionary Computation, 2006)

FPGA Implementation of Pulse Density Hopfield Neural Network. - Yutaka Maeda; Yoshinori Fukuda (IJCNN, 2007)

Simultaneous Perturbation Particle Swarm Optimization Using FPGA. - Yutaka Maeda; Naoto Matsushita (IJCNN, 2007)

Combination of particle swarm optimization and simultaneous perturbation. - Yutaka Maeda; Naoto Matsushita (IEEE Congress on Evolutionary Computation, 2008)

On simultaneous perturbation particle swarm optimization. - Yutaka Maeda; Naoto Matsushita; Seiji Miyoshi; Hiroomi Hikawa (IEEE Congress on Evolutionary Computation, 2009)

On automatic generation of VHDL code for self-organizing map. - Akira Onoo; Hiroomi Hikawa; Seiji Miyoshi; Yutaka Maeda (IJCNN, 2009)

Hand sign recognition system based on hybrid network classifier. - Yuuki Taki; Hiroomi Hikawa; Seiji Miyoshi; Yutaka Maeda (IJCNN, 2009)

Statistical Mechanical Analysis of Simultaneous Perturbation Learning. - Seiji Miyoshi; Hiroomi Hikawa; Yutaka Maeda (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2009)

Image compression with hardware self-organizing map. - Hiroomi Hikawa; Kenji Doumoto; Simone Miyoshi; Yutaka Maeda (IJCNN, 2010)

Comparison of range check classifier and hybrid network classifier for hand sign recognition system. - Hiroomi Hikawa; Seito Yamazaki; Tatsuya Ando; Simone Miyoshi; Yutaka Maeda (IJCNN, 2010)

Learning Scheme for Complex Neural Networks Using Simultaneous Perturbation. - Yutaka Maeda; Takahiro Yamada; Seiji Miyoshi; Hiroomi Hikawa (ICANN (2), 2011)

Statistical Mechanics of Adaptive Weight Perturbation Learning. - Ryosuke Miyoshi; Yutaka Maeda; Seiji Miyoshi (IEICE Trans. Inf. Syst., 2011)

Central pattern generator and its learning via simultaneous perturbation method. - Yutaka Maeda; Akihiro Ito; Hidetaka Ito (IJCNN, 2012)

Improved Learning Performance of Hardware Self-Organizing Map Using a Novel Neighborhood Function. - Hiroomi Hikawa; Yutaka Maeda (IEEE Trans. Neural Networks Learn. Syst., 2015)

A New Hardware Self-Organizing Map Architecture with High Expandability. - Hiroomi Hikawa; Hidetaka Ito; Yutaka Maeda (IPAS, 2018)

Hardware Self-Organizing Map Based on Frequency-Modulated Signal and Digital Frequency-Locked Loop. - Hiroomi Hikawa; Hidetaka Ito; Yutaka Maeda (ISCAS, 2018)

A New Self-Organizing Map with Continuous Learning Capability. - Hiroomi Hikawa; Hidetaka Ito; Yutaka Maeda (SSCI, 2018)

A Subspace Newton-Type Method for Approximating Transversely Repelling Chaotic Saddles. - Hidetaka Ito; Hiroomi Hikawa; Yutaka Maeda (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2018)

Learning Method of Recurrent Spiking Neural Networks to Realize Various Firing Patterns using Particle Swarm Optimization. - Yasuaki Kuroe; Hitoshi Iima; Yutaka Maeda (IJCCI, 2019)

Four Models of Hopfield-Type Octonion Neural Networks and Their Existing Conditions of Energy Functions. - Yasuaki Kuroe; Hitoshi Iima; Yutaka Maeda (IJCNN, 2020)

A Synthesis Method of Spiking Neural Oscillators with Considering Asymptotic Stability. - Yasuaki Kuroe; Seiji Miyoshi; Hiroomi Hikawa; Hidetaka Ito; Kimiko Motonaka; Yutaka Maeda (IJCNN, 2021)

Swarm Reinforcement Learning Method Based on Hierarchical Q-Learning. - Yasuaki Kuroe; Kenya Takeuchi; Yutaka Maeda (SSCI, 2021)