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Linearization of CMOS CCCII with Optimal Design via Geometric Programming
Roungsan Chaisricharoen,Boonruk Chipipop,Kosin Chamnongthai,Kohji Higuchi,Boonchareon Sirinaovakul 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
The mixed translinear loop, serving as the input stage of a CMOS CCCII, is analyzed in large signal method to examine the linearity condition, which is simply the matching between NMOS and PMOS loop components. Example configurations, providing linear and nonlinear V-I characteristic of input voltage and current, are simulated in the HSPICE based on the AMS’ 0.35μ CMOS process. The results verify the necessity of matching condition in designing a linear CMOS CCCII. To obtain an optimized design, the geometric programming is utilized based on attained perceptions. A sample requirement, also based on the AMS’ 0.35μ CMOS process, is globally optimized. The obtained solution is simulated in the HSPICE to verify the performances, which are satisfying the requirement quite well.
Rawid Banchuin,Boonruk Chipipop,Booncharoen Sirinaovakul 대한전자공학회 2007 ITC-CSCC :International Technical Conference on Ci Vol.2007 No.7
In this research, the effect of OTA’s major nonidealities entitled the parasitic elements and finite opened-loop bandwidth to the passive equivalent circuit of the structurally, practically higher performance OTA-based floating inductor which requires four OTAs i.e. 4-OTA based floating inductor, have been explored. The contributory results of this research have been found to be the derivation of an accurate passive equivalent circuit of the 4-OTA-based floating inductor under the effect of both major nonidealities which has been found to be a convenience tool for the design of any inductor substitution based analog circuits.
Forecasting the Effect of Stock Repurchase via an Artificial Neural Network
Karn Meesomsarn,Roungsan Chaisricharoen,Boonruk Chipipop,Thongchai Yooyativong 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
A simple static cascade-forward back-propagation artificial neural network (ANN) is utilized to forecast the effect of stock repurchase on the closing price of firm"s common stock. The input factors are composed of today"s closing price, index of the stock market and the amount of tomorrow-intended repurchase. A rule-based data clustering is used to group the repurchase days by selecting two records that are under the same conditions as the day before the next repurchase. A few initial predictions are less accurate than the classic accounting equation because the combinations of training set are very limited. However, after several repurchase days have passed, the ANN-based prediction usually introduces less error based on increasing amount of possible training sets. Therefore, this technique can be very useful if the repurchase is spanned in a quite long period.
Feasibility Determination of OTA for Active Floating Inductor Based Application
Rawid Banchuin,Roungsan Chaisricharoen,Boonruk Chipipop 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this research, the methodology for the feasibility determination of any candidate OTA for being used in active floating inductors based application, in the practical phenomena, has been proposed. The methodology can accurately determine the feasibility of any candidate OTA before directly applied to the cited application for prevent the unintentionally using the infeasible OTA. This methodology has been found to be very efficient, versatile and convenience since it can be performed even by hand calculation. Hence, with this methodology, the effort and the production cost of the signal processing equipments can be reduced.
Effective Per-Client Goodput Analysis of IEEE 802.11g Access Point under Full Client-Utilization
Roungsan Chaisricharoen,Thitiporn Pramoun,Boonruk Chipipop 대한전자공학회 2007 ITC-CSCC :International Technical Conference on Ci Vol.2007 No.7
To analyze the effective per-client goodput provided by IEEE 802.11g access point, the full factorial experiment is conducted under full client-utilization to observe its characteristics. From the experiment, the attenuation of the effective per-client goodput is reduced in non-linear manner as clients increase, which is contrast with the famous assumption of linear-reduction. In addition, the regression model, estimating the practical effective per-client goodput, is presented with adjusted R2 of 99.2%.