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Technical Committee on Nonlinear Problems (NLP) (Searched in: 2015)
Search Results: Keywords 'from:2015-05-18 to:2015-05-18'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP | 2015-05-18 13:30 |
Aomori | Yu-sa Asamushi | A Construction of Small State-Change Synchronization Algorithms Hiroshi Umeo, Keisuke Imai (OECU)  NLP2015-27 |
[more] | NLP2015-27 pp.1-5 |
| NLP | 2015-05-18 13:55 |
Aomori | Yu-sa Asamushi | Experimental verification of amplitude death in a delay-coupled oscillators network with fast time-varying topology Shinnosuke Masamura, Yoshiki Sugitani, Keiji Konishi, Naoyuki Hara (Osaka Pref. Univ.) NLP2015-28 |
[more] | NLP2015-28 pp.7-12 |
| NLP | 2015-05-18 14:30 |
Aomori | Yu-sa Asamushi | Virtualization of LTE Core Networks and Optimization of its Performance Kohei Hayashi, Hiroyuki Yasuda (Tokyo Univ. of Science), Yozo Shoji (NICT), Mikio Hasegawa (Tokyo Univ. of Science) NLP2015-29 |
Growing popularity of smartphones and tablet computers is making increase of signaling and processing load on mobile cor... [more] | NLP2015-29 pp.13-16 |
| NLP | 2015-05-18 14:55 |
Aomori | Yu-sa Asamushi | Analysis of basic mixed-rule cellular automata Naoki Tada, Toshimichi Saito (HU) NLP2015-30 |
This paper studies basic dynamics of mixed rules with cellular automata: a digital dynamical systems of discrete time a... [more] |
NLP2015-30 pp.17-21 |
| NLP | 2015-05-18 15:20 |
Aomori | Yu-sa Asamushi | A Method for Deciding Feasible Solution of Quadratic Assignment Problem from Mutually Connected Chaotic Neural Network Takafumi Matsuura (Nippon Inst. of Tech.), Tohru Ikeguchi (Tokyo Univ. Sci.) NLP2015-31 |
For finding good near-optimal solutions of quadratic assignment problems (QAPs), a heuristic method which uses a mutuall... [more] | NLP2015-31 pp.23-28 |
| NLP | 2015-05-18 15:55 |
Aomori | Yu-sa Asamushi | Basic performance of the fission artificial bee colony algorithm Hideto Sakamoto, Toshimichi Saito (HU) NLP2015-32 |
This paper presents an improved version of artificial bee colony algorithm and investigates its basic performance. Th... [more] |
NLP2015-32 pp.29-34 |
| NLP | 2015-05-18 16:20 |
Aomori | Yu-sa Asamushi | Controlling ON/OFF-Time in Switching Circuits Hiroyuki Asahara (Okayama Univ. of Science), Tetsushi Ueta (Tokushima Univ.), Daisuke Ito (The Univ. of Shiga Prefecture), Takuji Kousaka (Oita Univ.) NLP2015-33 |
[more] | NLP2015-33 pp.35-38 |
| NLP | 2015-05-19 10:00 |
Aomori | Yu-sa Asamushi | An Automatic Adjustment Method for Parameters in Deep Learning Kazuki Urushiyama, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2015-34 |
In this paper, we propose the method which tunes learning rate dynamically and breaks off learning automatically. In gen... [more] | NLP2015-34 pp.39-43 |
| NLP | 2015-05-19 10:25 |
Aomori | Yu-sa Asamushi | A Method for Determining Parameter Values of the Cochlea Reflectionless Transmission-Line Model Takemori Orima, Yoshihiko Horio (Tokyo Denki Univ.), Tohru Kohda (Kyushu Univ.) NLP2015-35 |
Cochlea models are good candidates for a high-performance frequency analyzer. The passive transmission-line model propos... [more] | NLP2015-35 pp.45-50 |
| NLP | 2015-05-19 11:00 |
Aomori | Yu-sa Asamushi | Relaxation oscillator which is driven by pulse wave with random pulse interval Takuya Kurihara, Kenya Jin'no (Nippon Inst. of Tech.) NLP2015-36 |
We study synchronization phenomena of relaxation oscillations induced by common external signals. The relaxation oscill... [more] |
NLP2015-36 pp.51-56 |
| NLP | 2015-05-19 11:25 |
Aomori | Yu-sa Asamushi | Dynamical property of asymmetric augmented Lorenz equations Kenichiro Cho, Takaya Miyano (Rits Univ) NLP2015-37 |
We have constructed nondimensionalized equations of motion of the turbine rotor for a chaotic gas turbine with two air i... [more] | NLP2015-37 pp.57-60 |
| NLP | 2015-05-19 11:50 |
Aomori | Yu-sa Asamushi | Basic Performances of Deterministic PSO Networks Tomoyuki Sasaki, Hidehiro Nakano, Arata Miyauchi, Akira Taguchi (Tokyo City Univ.) NLP2015-38 |
PSO network is the method of dividing population of PSO into multiple sub-swarm groups, and each sub-swarm group is conn... [more] | NLP2015-38 pp.61-66 |
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