Software defined radio (SDR) has been proposed as the solution to seamlessly support the existing and upcoming wireless communication standards. The fundamental idea of SDR is to replace the conventional analog signal processing in radio receivers with digital signal processing thus enabling the support of multiple communication standards by reconfiguration of the same hardware platform. SDR based cognitive radios (CRs) have the ability to sense the current spectrum utilization and change their behavioral and transmission characteristics dynamically so as to achieve efficient spectrum access. An important function in CRs is spectrum sensing, wherein the presence and (or) absence of channels of licensed users is to be detected in the wideband input signal in order to allow opportunistic access of the vacant frequency bands to the unlicensed users. In filter bank (FB) based spectrum sensing, the wideband input frequency range is split into uniform or non-uniform subbands using FBs and the presence of signals is then detected using techniques such as energy detection.

The channelizer, which consists of channel filters and FBs, is the most computationally intensive part of the SDR and CR based wireless communication receivers. In a typical CR, multiple radio channels corresponding to different wireless communication standards simultaneously coexist in the wideband input signal. These channels need to be accurately detected by the spectrum sensing block and then individually extracted by the channelizer, thus necessitating the ability to perform multi-standard channelization. Due to stringent area, power and cost specifications, channel filters and FBs that have low hardware resource utilization, low power consumption and high flexibility are desired for SDR and CR based wireless communication receivers.

Biography

Vinod Prasad received his B. Tech. degree from University of Calicut, India in 1993 and the M. Engg and Ph.D. degrees from School of Computer Engineering, Nanyang Technological University, Singapore in 2000 and 2004 respectively. He has spent the first 5 years of his career in industry as an automation engineer at Kirloskar (India), Tata Honeywell (India), and Shell (Singapore). He joined the School of Computer Engineering at Nanyang Technological University (NTU), Singapore, in 2002, where he is currently an Associate Professor. www.ntu.edu.sg/home/asvinod

Vinod.s research interests include digital signal processing (DSP), low power and reconfigurable DSP circuits, software defined radio, cognitive radio and brain-computer interface. He has secured research grants from Ministry of Education (Singapore), Ministry of Defense (Singapore), DSO National Labs, European Aeronautic Defence & Space Company (EADS) Singapore, Embassy of France in Singapore, UK High commission (Singapore) and Singapore Millennium Foundation (SMF), amounting over S$1.5 million as principal investigator. He has published about 160 research papers in refereed international journals and conferences. Currently, Vinod is leading a research team of 2 Postdoctoral Research Fellows and 7 PhD Students in Centre for High Performance Embedded Systems (CHiPES), NTU. He is a Senior Member of IEEE, Associate Editor of Circuits, Systems, and Signal Processing Journal (Springer), and an Editor of International Journal of Advancements in Computing Technology (IJACT). He has won the Nanyang Award for Excellence in Teaching in 2009, the highest recognition conferred by the University to individual faculty for teaching excellence.

Brain-Computer Interface (BCI) is an emerging technology that enables human brain to communicate with external world solely by brain signals, bypassing its normal output pathway of nerves and muscles. Capability of BCI for controlling external applications such as computer screen, wheel chair, robotic arm, neuroprosthetic devices etc. makes it a promising communication tool for paralyzed patients. Neural features in Electroencephalogram (EEG) related to the mental imagination of motor movement, termed motor imagery (MI), are potential candidates for developing EEG-based BCI. Activations in brain.s motor cortex during MI result in distinct EEG patterns. BCI performance is strongly correlated to accurate identification of the relevant features.

This talk will present some of the efficient algorithms which we proposed towards the development of MI-based BCI. A major challenge in any MI based BCI is the variability of MI patterns in temporal, spectral and spatial domains across different subjects over time. Our Discriminative Filterbank Common Spatial Pattern (DFBCSP) addresses the inter-subject variability of MI patterns by effectively estimating the subject-specific informative frequency bands for differentiating various MI tasks. Another new adaptive approach named as Adaptively Weighted Spectral Spatial Patterns (AWSSP) tracks the variability of the informative bands over time by adaptively computing the discriminative capability of various frequency components. Proposed methods offer higher BCI performance in terms of classification accuracy compared to the state-of art method. We have also proposed robust algorithms for classifying and decoding voluntary hand movement execution parameters such as direction and speed. The proposed Wavelet CSP (W-CSP) algorithm extracts low frequency components of EEG that encodes movement parameter information. Our Multiple Linear Regressor models can reconstruct the movement speed profile from W-CSP filtered EEG. The talk will also present preliminary results of our work to understand the effect of neurofeedback games on the cognitive skills of healthy subjects with the intention of developing serious games for treating attention-deficit children.

Biography

Vinod Prasad received his B. Tech. degree from University of Calicut, India in 1993 and the M. Engg and Ph.D. degrees from School of Computer Engineering, Nanyang Technological University, Singapore in 2000 and 2004 respectively. He has spent the first 5 years of his career in industry as an automation engineer at Kirloskar (India), Tata Honeywell (India), and Shell (Singapore). He joined the School of Computer Engineering at Nanyang Technological University (NTU), Singapore, in 2002, where he is currently an Associate Professor. www.ntu.edu.sg/home/asvinod

Vinod.s research interests include digital signal processing (DSP), low power and reconfigurable DSP circuits, software defined radio, cognitive radio and brain-computer interface. He has secured research grants from Ministry of Education (Singapore), Ministry of Defense (Singapore), DSO National Labs, European Aeronautic Defence & Space Company (EADS) Singapore, Embassy of France in Singapore, UK High commission (Singapore) and Singapore Millennium Foundation (SMF), amounting over S$1.5 million as principal investigator. He has published about 160 research papers in refereed international journals and conferences. Currently, Vinod is leading a research team of 2 Postdoctoral Research Fellows and 7 PhD Students in Centre for High Performance Embedded Systems (CHiPES), NTU. He is a Senior Member of IEEE, Associate Editor of Circuits, Systems, and Signal Processing Journal (Springer), and an Editor of International Journal of Advancements in Computing Technology (IJACT). He has won the Nanyang Award for Excellence in Teaching in 2009, the highest recognition conferred by the University to individual faculty for teaching excellence.