Design of low power SAR ADC in Biomedical Applications
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 7
Abstract
Power consumption is one of the main design constraints in today ICs. For systems that are powered by small non rechargeable batteries over the entire life time, such as medical implant devices ultra low power consumption is important. In these systems ADCs are key components to interface between analog world and digital domain. This project is going to address the design challenges and strategies of low power ADCs for biomedical implant devices.
Authors and Affiliations
Md. Kareemoddin , A. Ashok Kumar , Dr. Syed Musthak Ahmed
Keywords
Related Articles
- EP ID EP93524
- DOI -
- Views 87
- Downloads 0
Analysis of Sleep Mode Energy Consumption in CMOS Circuits Using Power Gating Switches
Analysis of Sleep Mode Energy Consumption in CMOS Circuits Using Power Gating Switches
QARS for Self Reconfiguration Mechanism in Wireless Mesh Networks
Wireless mesh networks (WMNs) are being developed actively and deployed widely for a variety of applications. Wireless Mesh Network (WMN) is a communication network made up of radio nodes organized in a mesh topo...
Distributional canonical sine transform by Using Gelfand-shilov technique
In this paper discussed the results on the topological structure of some of the S-type spaces of distributional canonical sine transform
A New Approach of Region Descriptor in content based image compression in medical applications
In this article the goal is to state a new algorithm demarcating regions and definer of regions in image processing applications. The study domain of this algorithm is the images derived from radiology in medical...
Study of ECG Signal Compression using modified discrete cosine and discrete wavelet transforms
A new hybrid two-stage electrocardiogram (ECG) signal compression method based on the modified discrete cosine transform (MDCT) and discrete wavelet transform (DWT) is proposed. The ECG signal is partitioned into blocks...