CONNECTION SPARSITY AND ORBIT STABILITY IN DYNAMIC BINARY NEURAL NETWORKS

Dynamic binary neural networks are recurrent type neural networks characterized by ternary connection parameters and signum activate function. Depending on the parameters, the network can generate various binary periodic orbits. The ternary connection parameters and signum activation function are suitable for precise analysis and hardware implementation. First, we investigate influence of connection sparsity on stability of a periodic orbit. As the sparsity increases, stability of a periodic orbit tends to be reinforced. As the sparsity increases further, stability tends to be weakened and various transient phenomena exist

recise analysis and evolutionary synthesis of sparse binary neural networks

研究成果の概要 (和文) : 3値結合とシグナム活性化関数で特徴づけられる動的バイナリーニューラルネットの解析と合成に関する基礎研究を行った。まず、3入力1出力ニューロンからなるスパースネットワークについて、回転タイプの周期軌道の安定性を解析した。そして、周期軌道の銘記と局所安定性を保証する合成法を構築した。次に、3層のネットワークについて、所望の周期軌道の銘記と、その安定性に関する理論を構築した。その理論に基づいて、任意の周期軌道の銘記と、その大域安定性を保証する合成法を構築した。さらに、ネットワークをFPGA上にハードウエア実装し、周期軌道を実現し、6足ロボットの歩行パターンの制御に応用した。研究成果の概要 (英文) : We have studied analysis and synthesis of dynamic binary neural networks characterized by ternary connection parameters and the signum activation function. First, in simple sparse networks (consisting of neurons from three inputs to one output), we have analyzed stability of rotation-type periodic orbits. Based on the analysis results, we have constructed a synthesis method that guarantees storage and local stability of the rotation-type periodic orbits. Second, in three-layer networks, we have given a basic theoretical result on storage and stability of desired periodic orbits. Based on the theory, we have constructed a synthesis method that guarantees storage and global stability of any desired periodic orbits. Third, implementing the networks on FPGA board, periodic orbits have been confirmed experimentally. The FPGA based hardware has applied to control of walking patterns in hexapod robots

Analysis of 3D printed NDFeB polymer bonded and organic based magnets

Additive manufacturing (AM), or commonly known as 3D printing, has introduced to the manufacturing and commercial sectors novel ways of reducing production times, decreasing material waste, and enabling end products with multi-material configuration and complex geometric designs. From industrial scale to customer-based printers, AM has revolutionized the approach to manufacturing, prototyping, and designing in the field of medical, automotive, aerospace, biomedical, electronics and customizable products. Recently, additive manufacturing has crossed over to the area of applications in magnetism due to the economic push for the miniaturization of electronic and mechanical devices, reduction in production costs and material & design flexibility. The goal of this research is to add to the groundwork for the additive manufacturing with NdFeB bonded and organic based magnetic materials. Development of 3D printing methods will open doors to new applications in magnetism and will lead to significant opportunities in its applications. NdFeB bonded composites and organic based magnetic materials will be converted to feedstock and implemented into the 3D printer to fabricate magnetic objects with complex and unique shapes. The molecular, electronic and structural properties of these materials will be characterized using various analytical and physical methods and the results will be compared