A New Structure of Current Mode Min-Max Circuit Using CMOS Technology for Fuzzy Applications

被引:0
|
作者
Khayatzadeh, Ramin [1 ]
Yazdani, Ghasem [1 ]
Khoie, Abdollah [1 ]
Hadidi, Khayrollah [1 ]
机构
[1] Urmia Univ, Microelect Res Lab, Orumiyeh 57159, Iran
来源
2014 22ND IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE) | 2014年
关键词
CMOS; current mode; min-max;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper a new structure of current mode min-max circuit is presented. The proposed structure can detect minimum and maximum of the input current signals simultaneously. It has advantages of analog design such as 1.5 percent error in maximum amplitude and low power consumption. Hence, the proposed circuit has high precision. The proffered circuit involves 14+4 transistors using 0.18um CMOS standard technology. A 1.8 (V) power supply is applied and the Monte Carlo, corner, pulse and other simulations for checking performances of the proposed circuit have been done using HSPICE level49 (BSIM3v3) software. Also, the layout pattern of the proposed circuit is drawn by CADENCE software.
引用
收藏
页码:346 / 350
页数:5
相关论文
共 50 条
  • [21] Color image segmentation using fuzzy min-max neural networks
    Estévez, PA
    Flores, RJ
    Perez, CA
    Proceedings of the International Joint Conference on Neural Networks (IJCNN), Vols 1-5, 2005, : 3052 - 3057
  • [22] Transfer learning using the online Fuzzy Min-Max neural network
    Seera, Manjeevan
    Lim, Chee Peng
    NEURAL COMPUTING & APPLICATIONS, 2014, 25 (02): : 469 - 480
  • [23] Adaptive Color Image Segmentation Using Fuzzy Min-Max Clustering
    Deshmukh, A. Kanchan
    Shinde, B. Ganesh
    ENGINEERING LETTERS, 2006, 13 (02)
  • [24] Reinforcement learning using the stochastic fuzzy min-max neural network
    Likas, A
    NEURAL PROCESSING LETTERS, 2001, 13 (03) : 213 - 220
  • [25] Data Clustering Using a Modified Fuzzy Min-Max Neural Network
    Seera, Manjeevan
    Lim, Chee Peng
    Loo, Chu Kiong
    Jain, Lakhmi C.
    SOFT COMPUTING APPLICATIONS, (SOFA 2014), VOL 1, 2016, 356 : 413 - 422
  • [26] A New CMOS Current-Mode Classifier Circuit for Statistics Applications
    Popa, Cosmin
    NN'09: PROCEEDINGS OF THE 10TH WSEAS INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, 2009, : 17 - 20
  • [27] Pattern Classification using Modified Enhanced Fuzzy Min-Max Neural Network
    Landge, Chaitrali B.
    Shinde, Swati V.
    2016 INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA), 2016,
  • [28] Emotion Recognition using Prosody Features and a Fuzzy Min-Max Neural Classifier
    Jawarkar, N. P.
    IETE TECHNICAL REVIEW, 2007, 24 (05) : 369 - 373
  • [29] Retinal vessel segmentation using enhanced fuzzy min-max neural network
    Biyani, R. S.
    Patre, B. M.
    Kulkarni, U. V.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (24) : 35053 - 35073
  • [30] Design of a fuzzy min-max hyperbox classifier using a supervised learning method
    Chen, CC
    CYBERNETICS AND SYSTEMS, 2006, 37 (04) : 329 - 346