• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.361-367
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• 2014

This paper introduces balancing energy and memory consumption for lifetime increase of wireless sensor network. In cluster-based wireless sensor network, sensor nodes adjacent of cluster heads have a tendency to deplete their own battery energy and cluster heads occupy memory space significantly. If the nodes close to region where events occur frequently consume their energy and memory fully, network might be destroyed even though most of nodes are still alive. Therefore, it needs to balance network energy and memory with consideration of event occurrence probability so that network lifetime is increased. We show a method of balancing wireless sensor network energy and memory to organize cluster groups and elect cluster heads in terms of event occurrence probability.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.10 s.101
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• pp.1010-1019
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• 2005

In this paper, we used neural network technique to model memory effects of RF power amplifier which is fed by two-tone input signals. The memory effects in power amplifier were identified by observing the unsymmetrical distribution of IMD(Inter-Modulation Distortion) measurements with the change of tone spacings and power levels. Different asymmetries of IMD were also found at different center frequencies. We applied TDNN technique to model LDMOS power amplifier based on two tone IMD data, and the accuracy was very high compared to other modeling methods such as the(memoryless) adaptive modeling method.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.470-472
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• 1987

This paper deals with the continuous-discrete estimation problem using FIR filters and performs modeling error analyses of the FIR filters, compared to Kalman filter and the limited memory filters, via computer simulations. It is shown that, the less driving noise the system has, the better performance the FIR filter exhibits and that this characteristic appears rare distinctly in nonlinear system than in linear systems.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.2
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• pp.59-66
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• 2013

In this paper, we proposed an optimal ILP algorithm on memory address code generation for DSP in embedded system. This paper using 0-1 ILP formulations DSP address generation units should minimize the memory variable data layout. We identify the possibility of the memory assignment of variable based on the constraints condition, and register the address code which a variable instructs in the program pointer. If the process sequence of the program is declared to the program pointer, then we apply the auto-in/decrement mode about the address code of the relevant variable. And we minimize the loads on the address registers to optimize the data layout of the variable. In this paper, in order to prove the effectiveness of the proposed algorithm, FICO Xpress-MP Modeling Tools were applied to the benchmark. The result that we apply a benchmark, an optimal memory layout of the proposed algorithm then the general declarative order memory on the address/modify register to reduce the number of loads, and reduced access to the address code. Therefor, we proved to reduce the execution time of programs.

• Psychiatry investigation
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• v.15 no.12
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• pp.1154-1161
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• 2018

Objective The present study aimed to investigate relationship among cognitive factors (working memory and processing speed) and fluid reasoning (Gf) in psychiatric patients using a standardized clinical tool. Methods We included the responses of 115 heterogeneous patients who were diagnosed with the MINI-Plus 5.0 and WAIS-IV/WMS-IV was administered. For our analysis, structured equation modeling (SEM) was conducted to evaluate which cognitive variables are closely related to the Gf. Results The results showed that the visual working memory was the strongest predictor of the Gf compared to other cognitive factors. Conclusion Processing speed was capable of predicting the Gf, when visual working memory was controlled. The inter-relationship among the Gf and other cognitive factors and its clinical implications were further discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.488-491
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• 1997

The PMGS(Plant Model Generating System) was developed based on modular modeling method and fluid network calculation concept. Fluid network calculation is used as a method of real-time computation of fluid network, and the module which has a topology with node and branch is defined to take advantages of modular modeling. Also, the database which have a shared memory as an instance is designed to manage simulation data in real-time. The applicability of the PMGS was examined implementing the HRSG(Heat Recovery Steam Generator) control logic on DCS.

• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.23-37
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• 2022

Purpose - The purpose of this paper is to analyze the dynamic factors of the daily FX implied volatility based on the fractional integration methods focusing on long memory feature and structural changes. Design/methodology/approach - This paper uses the daily FX implied volatility data of the EUR-USD and the JPY-USD exchange rates. For the fractional integration analysis, this paper first applies the basic ARFIMA-FIGARCH model and the Local Whittle method to explore the long memory feature in the implied volatility series. Then, this paper employs the Adaptive-ARFIMA-Adaptive-FIGARCH model with a flexible Fourier form to allow for the structural changes with the long memory feature in the implied volatility series. Findings - This paper finds statistical evidence of the long memory feature in the first two moments of the implied volatility series. And, this paper shows that the structural changes appear to be an important factor and that neglecting the structural changes may lead to an upward bias in the long memory feature of the implied volatility series. Research implications or Originality - The implied volatility has widely been believed to be the market's best forecast regarding the future volatility in FX markets, and modeling the evolution of the implied volatility is quite important as it has clear implications for the behavior of the exchange rates in FX markets. The Adaptive-ARFIMA-Adaptive-FIGARCH model could be an excellent description for the FX implied volatility series

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.7
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• pp.1-9
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• 2011

Memristor is a portmanteau of "memory resistor". The resistance of memristor is changed depends on the history of electric charge that passed through the device and it is able to memorize the last resistance after turning off the power supply. This paper presents this device that has a high chance to be the next generation of commercial non-volatile memory and its behavior modeling using SPICE simulation. The memristor MOS content addressable memory (M_CAM) is also designed and simulated using the proposed behavioral model. The proposed M_CAM unit cell area and power consumption show an improvement around 40% and 96%, respectively, compare to the conventional SRAM based CAMs. The M_CAM layout is also implemented using 0.13${\mu}m$ mixed-signal CMOS process under 1.2 V supply voltage.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.736-746
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• 2002

There has been a great demand for smart actuators in the field of micro-machines. However, the control accuracy of smart actuators, e.g., a shape memory alloy(SMA) and a piezoceramic actuator, is limited due to the inherent hysteresis nonlinearity. The Preisach hysteresis model has emerged as an appropriate model f3r the behavior of those smart actuators. Yet it is still not easy to construct a practical model of hysteresis using the classical Preisach model. Accordingly, in this paper, we propose a new simple method for modeling of the hysteresis nonlinearity of SMA. Using only the proportional relation of the major loop of hysteresis, the proposed method makes the computation of the Preisach model easy. We prove the efficacy of the proposed model through the comparative the experimentation with the classical Preisach model.

• Smart Structures and Systems
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• v.18 no.4
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• pp.663-682
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• 2016

Continuum manipulators as a kind of mechanical arms are useful tools in special robotic applications. In medical applications, like colonoscopy, a maneuverable thin and flexible manipulator is required. This research is focused on developing a basic module for such an application using shape memory alloys (SMA). In the structure of the module three wires of SMA are uniformly distributed and attached to the circumference of a flexible tube. By activating wires, individually or together, different rotation regimes are provided. SMA model is used based on Brinson work. The SMA model is combined to model of flexible tube to provide a composite model of the module. Simulating the model in Matlab provided a platform to be used to develop controller. Complex and nonlinear behavior of SMA make the control problem hard especially when a few SMA actuators are active simultaneously. In this paper, position control of the two degree of freedom module is under focus. An experimental control strategy is developed to regulate a desired position in the module. The simulation results present a reasonable performance of the controller. Moreover, the results are verified through experiments and show that the continuum module of this paper would be used in real modular manipulators.