1 0 0 0 OA 圧縮センシングにおける完全再現十分条件について
- 著者
- 和田山 正
- 出版者
- 日本神経回路学会
- 雑誌
- 日本神経回路学会誌 (ISSN:1340766X)
- 巻号頁・発行日
- vol.17, no.2, pp.63-69, 2010-06-05 (Released:2010-07-30)
- 参考文献数
- 7
圧縮センシング(compressed sensing)は,スパース信号に対するサンプリング理論である.ランダム線形測定過程により得られるサンプル信号からの原信号の再現可能性,計算量の少ない再現アルゴリズムの構成が圧縮センシングの重要な研究テーマとなっている.本解説では,Candes-Taoらによる原信号完全再現のための十分条件について解説を行う.
1 0 0 0 OA 大脳皮質のGABA作働性神経回路
- 著者
- 川口 泰雄
- 出版者
- 日本神経回路学会
- 雑誌
- 日本神経回路学会誌 (ISSN:1340766X)
- 巻号頁・発行日
- vol.5, no.4, pp.171-177, 1998-12-05 (Released:2011-01-17)
- 参考文献数
- 40
To understand the inhibitory network in the cortex, we have started to clarify several features of GABAergic neurons in the frontal cortex of rats. These are; (1) the physiological, chemical and morphological characteristics of cortical GABAergic neurons to identify the subtypes, (2) the synaptic connections among these neuronal subtypes and (3) the synaptic properties and the chemical modulation of each subtype. An experimental approach in which multiple properties of a GABA neuron are determined for the same cell, yields a set of data which allows a more comprehensive classification of the neuron as an element of a local neuronal circuit.
1 0 0 0 OA 脳研究における仮想実験
1 0 0 0 OA カーネルマシンへの高速ベクトル量子化の導入
- 著者
- 笠井 航 長谷川 修
- 出版者
- 日本神経回路学会
- 雑誌
- 日本神経回路学会誌 (ISSN:1340766X)
- 巻号頁・発行日
- vol.16, no.3, pp.149-157, 2009-09-05 (Released:2009-10-30)
- 参考文献数
- 22
- 被引用文献数
- 3 2
In this paper, we propose a fast learning algorithm of a support vector machine (SVM). Our work is based on the Learning Vector Quantization (LVQ) and we compress the data to perform properly in the context of clustered data margin maximization. For solving the problem faster, we propose the improved TOD algorithm, which is one of the simplest form of LVQ. Experimental results demonstrate that our method is as accurate as the existing implementation, but it is faster in most situations. We also show the extension of the proposed learning framework for online re-training problem.
1 0 0 0 OA ポストヒューマンは誕生するか?
- 著者
- 鈴木 良次
- 出版者
- 日本神経回路学会
- 雑誌
- 日本神経回路学会誌 (ISSN:1340766X)
- 巻号頁・発行日
- vol.16, no.2, pp.61-63, 2009-06-05 (Released:2009-08-14)
1 0 0 0 OA 競合連想ネットによる距離画像からの平面抽出
- 著者
- 黒木 秀一 西田 健
- 出版者
- 日本神経回路学会
- 雑誌
- 日本神経回路学会誌 (ISSN:1340766X)
- 巻号頁・発行日
- vol.14, no.4, pp.273-281, 2007-12-05 (Released:2008-11-21)
- 参考文献数
- 20
- 被引用文献数
- 1
This paper describes an application of the competitive associative net called CAN2 to plane extraction from range images measured by a laser range scanner (LRS). The CAN2 basically is a neural net for learning efficient piecewise linear approximation of nonlinear functions, and in this application it is utilized for learning piecewise planner (linear) surfaces from the range image. As a result of the learning, the obtained piecewise planner surfaces are more precise than the actual planner surfaces, so that we introduce a method to gather piecewise planner surfaces for reconstructing the actual planner surfaces. We apply this method to the real range image, and examine the effectiveness by means of comparing other methods, such as the USF (University of South Florida) method and a RHT (Randomized Hough Transform) based method.
