Fast-slow asymptotics for a Markov chain model of fast sodium current

We explore the feasibility of using fast-slow asymptotic to eliminate the computational stiffness of the discrete-state, continuous-time deterministic Markov chain models of ionic channels underlying cardiac excitability. We focus on a Markov chain model of the fast sodium current, and investigate its asymptotic behaviour with respect to small parameters identified in different ways.Comment: 16 pages, 6 figures, as accepted to Chaos 2017/09/0

A Hidden Markov Factor Analysis Framework for Seizure Detection in Epilepsy Patients

Approximately 1% of the world population suffers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. Detection of seizure from the recorded EEG is a laborious, time consuming and expensive task. In this study, we propose an automated seizure detection framework to assist electroencephalographers and physicians with identification of seizures in recorded EEG signals. In addition, an automated seizure detection algorithm can be used for treatment through automatic intervention during the seizure activity and on time triggering of the injection of a radiotracer to localize the seizure activity. In this study, we developed and tested a hidden Markov factor analysis (HMFA) framework for automated seizure detection based on different features such as total effective inflow which is calculated based on connectivity measures between different sites of the brain. The algorithm was tested on long-term (2.4-7.66 days) continuous sEEG recordings from three patients and a total of 16 seizures, producing a mean sensitivity of 96.3% across all seizures, a mean specificity of 3.47 false positives per hour, and a mean latency of 3.7 seconds form the actual seizure onset. The latency was negative for a few of the seizures which implies the proposed method detects the seizure prior to its onset. This is an indication that with some extension the proposed method is capable of seizure prediction

Improved Spectrum Mobility using Virtual Reservation in Collaborative Cognitive Radio Networks

Cognitive radio technology would enable a set of secondary users (SU) to opportunistically use the spectrum licensed to a primary user (PU). On the appearance of this PU on a specific frequency band, any SU occupying this band should free it for PUs. Typically, SUs may collaborate to reduce the impact of cognitive users on the primary network and to improve the performance of the SUs. In this paper, we propose and analyze the performance of virtual reservation in collaborative cognitive networks. Virtual reservation is a novel link maintenance strategy that aims to maximize the throughput of the cognitive network through full spectrum utilization. Our performance evaluation shows significant improvements not only in the SUs blocking and forced termination probabilities but also in the throughput of cognitive users.Comment: 7 pages, 10 figures, IEEE ISCC 201

A radio channel emulator for WCDMA, based on the hidden Markov model (HMM)

One of the main development and research subjects within the telecommunications area activity is the 3G mobile systems standardisation. The radio access is, of course, the main trouble in mobile systems, so it is important to investigate its implication. This paper describes a radio channel emulator for the UTRA-FDD made, based on the hidden Markov model (HMM). Since a statistical system behaviour is needed to train the HMM, off-line simulations have been made. The results between simulated and emulated statistics are presented. The use of emulation models implies a loss of accuracy with respect to simulation models, but is adequate to operate in real time. Certainly, the main advantage of using HMM in the emulator is the huge reduction in time, resources and effort with regard to a real simulation of the system. The emulator will allow in future works, for fast testing and comparison of several higher layer protocols and error control schemes.Peer ReviewedPostprint (published version