Tuning of a Capacitorless Bandpass Biquad through Sequentially Trained ANN

摘要：

The sequential trained artificial neural network (ANN) based on updated training sets is successfully deployed to tune a capacitorless all-OTA bandpass biquad. The training set contains less than a few tens samples which are selected from predefine bias points that are closed to the desired biquad requirement. To limit training time,the less complex ANN is recommended.Feasibility of a biquad requirement is easily indicated by observing the maximum error of the worst element in an initial training set. A second order bandpass requirement,centered at 406.2 MHz,is successfully tuned as a sample. The proposed feasibility analysis and tuning process are tested with one hundred random bandpass requirements. As there is no indication of type-Ⅰ and type-Ⅱ errors,the proposed process is considered very efficient.

关键词： capacitorless ANN bandpass biquad

作者: Montira Moonngam Roungsan Chaisricharoen Boonruk Chipipop

作者单位: VLSI & AI laboratory,Department of Computer Engineering,Faculty of Engineering,King Mongkuts Univer School of Information Technology,Mae Fah Luang University,Chiang Rai 57100,Thailand

会议类型: 国际会议

会议名称: 2009 IEEE 8th International Conference on ASIC(第八届IEEE国际专用集成电路大会)

会议地点: 长沙

会议语种:英文

页码: 280-283

在线出版日期: 2009-10-20（万方平台首次上网日期，不代表论文的发表时间）