• ETRI Journal
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• v.30 no.6
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• pp.783-789
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• 2008

A bio-inspired vision chip for edge detection was fabricated using 0.35 ${\mu}m$ double-poly four-metal complementary metal-oxide-semiconductor technology. It mimics the edge detection mechanism of a biological retina. This type of vision chip offer several advantages including compact size, high speed, and dense system integration. Low resolution and relatively high power consumption are common limitations of these chips because of their complex circuit structure. We have tried to overcome these problems by rearranging and simplifying their circuits. A vision chip of $160{\times}120$ pixels has been fabricated in $5{\times}5\;mm^2$ silicon die. It shows less than 10 mW of power consumption.

• Journal of IKEEE
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• v.23 no.2
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• pp.403-406
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• 2019

We propose a low-loss on-chip transformer using an auxiliary primary part (APP) for an output matching network for fully integrated CMOS power amplifiers. The APP is designed using a fifth metal layer while the primary and secondary parts are designed using a sixth metal layer with a width smaller than that of the primary and secondary parts of the transformer to minimize the substrate loss and the parasitic capacitance between the primary and secondary parts. By adapting the APP in the on-chip transformer, we obtain an improved maximum available gain value without the need for any additional chip area. The feasibility of the proposed APP structure is successfully verified.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.83-93
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• 2014

It is a widespread concern that electrical interconnection based network-on-chip (NoC) will ultimately face the limitation in communication bandwidth, transmission latency and power consumption in the near future. With the development of silicon photonics technology, a hybrid optical network-on-chip (HONoC) which embraces both electrical- and optical interconnect, is emerging as a promising solution to overcome these problems. Today's leading edge systems-on-chips (SoCs) comprise heterogeneous many-cores for higher energy efficiency, therefore, extended study beyond regular topology based NoC is required. This paper proposes an energy and latency optimization topology design technique for HONoC taking into account the traffic characteristics of target applications. The proposed technique is implemented with genetic algorithm and simulation results show the reduction by 13.84% in power loss and 28.14% in average latency, respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.11
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• pp.56-65
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• 2009

As increasing the number of IPs integrated in a single chip and requiring high communication bandwidth on a chip, the trend of SoC communication architecture is changed from bus- or crossbar-based architecture to packet switched network architecture, NoC. However, highly complex control logics in routers require multiple cycles to switch packet. In this paper, we design low complex router to improve the communication latency. Our NoC design is verified by simulation platform modeled by ESL tool, SoC Designer. We also evaluate our NoC design comparing to the previous NoC architecture based on VC router. Our results show that our NoC architecture has less communication latency, even small throughput degradation (about 1-2%).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.459-461
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• 2022

One of the big differences between Network-on-Chip (NoC) and the existing parallel processing system based on an off-chip network is that data packet routing is performed using a centralized control scheme. In such an environment, the best-effort packet routing problem becomes a real-time assignment problem in which data packet arriving time and processing time is the cost. In this paper, the Hungarian algorithm, a representative computational complexity reduction algorithm for the linear algebraic equation of the allocation problem, is implemented in the form of a hardware accelerator. As a result of logic synthesis using the TSMC 0.18um standard cell library, the area of the circuit designed through case analysis for the cost distribution is reduced by about 16% and the propagation delay of it is reduced by about 52%, compared to the circuit implementing the original operation sequence of the Hungarian algorithm.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.190-193
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• 2009

The most essential element in wireless sensor network is wireless sensor node which collects environmental information and transmits it to the user application systems. Recently, due to the technological advancement, wireless sensor nodes are become smaller, more intelligent and less power consuming. Especially, SoC(System-on-Chip) technology, which unifies the MCU, RF module, memory and other element inside one chip, plays an important part for miniaturization of sensor node, hence reduces the manufacturing expenses. In this paper, we have designed a miniaturized wireless sensor node for wireless sensor network using commercial SoC technology and discussed about some application scenario and additional considerations.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.1
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• pp.20-27
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• 2008

In this paper, a nonlinear classifier of a feed-forward neural network is implemented on an FPGA chip. The feedforward neural network is implemented in hardware for fast parallel processing. After off line training of neural network, weight values are saved and used to perform forward propagation of neural processing. As an example, AND and XOR digital logic classification is conducted in off line, and then weight values are used in neural network. Experiments are conducted successfully and confirmed that the FPGA neural network hardware works well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1128-1133
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• 2008

Context-aware computing has been attracting the attention as an approach to alleviating the inconvenience in human-computer interactions. This paper proposes a context-aware system architecture to be implemented on an UoC (Ubiquitous system on Chip). A new proposed technology of CRS (Context Recognition Switch) and DOS (Dynamic and Optimal Standard) based on Context-awareness system architecture with pre-processor, HPSP(High Performance Signal Processor) in this paper. And proposed a new algorithm using in network topology processor shows for Ubiquitous Computing System. implementing in UoC (Ubiquitous System on Chip) base on the IEEE 802.15.4 WPAN (Wireless Personal Area Network) standard. Also, This context-aware based UoC architecture has been developed to apply to mobile intelligent robots which would support human in a context-aware manner.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2059-2063
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• 2009

This paper presents a programmable System-On-a-chip (SoC) for various embedded smart applications that need Neural Network computations. The system is fully implemented into a prototyping platform based on Field Programmable Gate Array (FPGA). The SoC consists of an embedded processor core and a reconfigurable hardware accelerator for neural computations. The performance of the SoC is evaluated using a real image processing application, an optical character recognition (OCR) system.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.68-75
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• 2016

As the number of cores and IPs increase in multiprocessor system-on-chip (MPSoC), network-on-chip (NoC) has emerged as a promising novel interconnection architecture for its parallelism and scalability. However, minimization of the latency in NoC with legacy bus IPs must be addressed. In this paper, we focus on the latency minimization problem in NoC which accommodates legacy bus protocol based IPs considering the trade-offs between hop counts and path collisions. To resolve this problem, we propose separated address/data network for independent address and data phases of bus protocol. Compared to Mesh and irregular topologies generated by TopGen, experimental results show that average latency and execution time are reduced by 19.46% and 10.55%, respectively.