Junji Kitamichi

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A novel neural network approach called gradual neural network (GNN) is presented for segmented channel routing in field programmable gate arrays (FPGA's). FPGA's contain predefined segmented channels for net routing, where adjacent segments in a track can be interconnected through programmable switches for longer segments. The goal of the FPGA segmented(More)
A novel neural network approach called "Evolutionary Neural Network (ENN)" is presented for the module orientation problem. The goal of this NP-complete problem is to minimize the total wire length by flipping circuit modules with respect to their vertical and/or horizontal axes of symmetry. In order to achieve high quality VLSI systems, it is strongly(More)
— In this paper, we propose a library for the system level modeling and simulation of the system which includes Dynamically Reconfigurable Architectures(DRAs). The proposed library is an extended SystemC library. Using the proposed library, the designer can model the system specifications including modules for the dynamic generation and elimination and(More)
A gradual neural network (GNN) algorithm is presented for the jointly time-slot/code assignment problem (JTCAP) in a packet radio network in this paper. The goal of this newly defined problem is to find a simultaneous assignment of a time-slot and a code to each communication link, whereas time-slots and codes have been independently assigned in existing(More)
In this paper, we propose a new type of sensor network called the demand-addressable sensor network (DASN). DASN actively gets desired information by delivering or addressing users' demands to appropriate places that are expected to have the information. This is in contrast to conventional sensor networks, which simply send sensed data to users. DASN is(More)