Data-driven multivariate and multiscale methods for brain computer interface

This thesis focuses on the development of data-driven multivariate and multiscale methods for brain computer interface (BCI) systems. The electroencephalogram (EEG), the most convenient means to measure neurophysiological activity due to its noninvasive nature, is mainly considered. The nonlinearity and nonstationarity inherent in EEG and its multichannel recording nature require a new set of data-driven multivariate techniques to estimate more accurately features for enhanced BCI operation. Also, a long term goal is to enable an alternative EEG recording strategy for achieving long-term and portable monitoring. Empirical mode decomposition (EMD) and local mean decomposition (LMD), fully data-driven adaptive tools, are considered to decompose the nonlinear and nonstationary EEG signal into a set of components which are highly localised in time and frequency. It is shown that the complex and multivariate extensions of EMD, which can exploit common oscillatory modes within multivariate (multichannel) data, can be used to accurately estimate and compare the amplitude and phase information among multiple sources, a key for the feature extraction of BCI system. A complex extension of local mean decomposition is also introduced and its operation is illustrated on two channel neuronal spike streams. Common spatial pattern (CSP), a standard feature extraction technique for BCI application, is also extended to complex domain using the augmented complex statistics. Depending on the circularity/noncircularity of a complex signal, one of the complex CSP algorithms can be chosen to produce the best classification performance between two different EEG classes. Using these complex and multivariate algorithms, two cognitive brain studies are investigated for more natural and intuitive design of advanced BCI systems. Firstly, a Yarbus-style auditory selective attention experiment is introduced to measure the user attention to a sound source among a mixture of sound stimuli, which is aimed at improving the usefulness of hearing instruments such as hearing aid. Secondly, emotion experiments elicited by taste and taste recall are examined to determine the pleasure and displeasure of a food for the implementation of affective computing. The separation between two emotional responses is examined using real and complex-valued common spatial pattern methods. Finally, we introduce a novel approach to brain monitoring based on EEG recordings from within the ear canal, embedded on a custom made hearing aid earplug. The new platform promises the possibility of both short- and long-term continuous use for standard brain monitoring and interfacing applications

A Space Communications Study Final Report, Sep. 15, 1965 - Sep. 15, 1966

Reception of frequency modulated signals passed through deterministic and random time-varying channel

Advanced methods in automatic modulation classification for emerging technologies

Modulation classification (MC) is of large importance in both military and commercial communication applications. It is a challenging problem, especially in non-cooperative wireless environments, where channel fading and no prior knowledge on the incoming signal are major factors that deteriorate the reception performance. Although the average likelihood ratio test method can provide an optimal solution to the MC problem with unknown parameters, it suffers from high computational complexity and in some cases mathematical intractability. Instead, in this research, an array-based quasi-hybrid likelihood ratio test (qHLRT) algorithm is proposed, which depicts two major advantages. First, it is simple yet accurate enough parameter estimation with reduced complexity. Second the incorporation of antenna arrays offers an effective ability to combat fading. Furthermore, a practical array-based qHLRT classifier scheme is implemented, which applies maximal ratio combining (MRC) to increase the accuracy of both carrier frequency offset (CFO) estimation and likelihood function calculation in channel fading. In fact, double CFO estimations are executed in this classifier. With the first the unknown CFO, phase offsets and amplitudes are estimated as prerequisite for MRC operation. Then, MRC is performed using these estimates, followed by a second CFO estimator. Since the input of the second CFO estimator is the output of the MRC, fading effects on the incoming signals are removed significantly and signal-to-noise ratio (SNR) is augmented. As a result, a more accurate CFO estimate is obtained. Consequently, the overall classification performance is improved, especially in low SNR environment. Recently, many state-of-the-arts communication technologies, such as orthogonal frequency division multiplexing (OFDM) modulations, have been emerging. The need for distinguishing OFDM signal from single carrier has become obvious. Besides, some vital parameters of OFDM signals should be extracted for further processing. In comparison to the research on MC for single carrier single antenna transmission, much less attention has been paid to the MC for emerging modulation methods. A comprehensive classification system is proposed for recognizing the OFDM signal and extracting its parameters. An automatic OFDM modulation classifier is proposed, which is based on the goodness-of-fittest. Since OFDM signal is Gaussian, Cramer-von Mises technique, working on the empirical distribution function, has been applied to test the presence of the normality. Numerical results show that such approach can successfully identify OFDM signals from single carrier modulations over a wide SNR range. Moreover, the proposed scheme can provide the acceptable performance when frequency-selective fading is present. Correlation test is then applied to estimate OFDM cyclic prefix duration. A two-phase searching scheme, which is based on Fast Fourier Transform (FFT) as well as Gaussianity test, is devised to detect the number of subcarriers. In the first phase, a coarse search is carried out iteratively. The exact number of subcarriers is determined by the fine tune in the second phase. Both analytical work and numerical results are presented to verify the efficiency of the proposed scheme

Secure Communications Systems Utilizing Pseudo-Noise Carriers and Sub-carriers

The current literature approaches the subject of communications from the optimum detector point of view, utilizing the principles set forth by Shannon, Davenport, Root, Bode, Peterson, Birdsall, Fox, Weiner, Siebert, Middleton, and many others to carry out detailed analysis of specific detectors, filters, and synchronization processes. This paper approaches communications from a systems point of view, dealing specifically with the family of pseudo-noise systems. The systems discussed are categorized into two groups, the pseudo-noise carrier and the pseudo-noise sub-carrier systems, with emphasis on multiplex techniques. All of the systems discussed are negative dB S/N systems with the exception of a wide-band TV video channel, and a detailed analysis of a representative pseudo-noise sequence of length 15 is given as a background in the auto-correlation functions, power spectral densities, and self-noise spectra which are the characterizing parameters of these waveforms.Lieutenant, United States NavyApproved for public release; distribution is unlimited

Neural Adaptation and the Effect of Interelectrode Spacing on Epidural Electrocorticography for Brain-Computer Interfaces

Electrocorticography: ECoG) is increasingly being identified as a safe and reliable recording technique for both Brain-Computer Interface: BCI) applications as well as neurophysiology studies. This thesis describes some of the first real-time closed-loop BCI studies of chronic ECoG in non-human primates. Epidural microECoG electrodes developed in our lab were implanted in three monkeys with the electrode array centered over primary motor cortex: M1). Monkeys were then trained to perform a one-dimensional BCI task. The BCI control scheme was independent of any prior screening for task-related activity. All three monkeys successfully learned to perform the task with multiple control configurations and each time gained significant performance in 10 days or less. Interelectrode distance between control electrodes was also tested for three different distances. 15 and 9 mm spacing resulted in equivalent performance while 3 mm saw a moderate but significant degradation in performance. Finally, post hoc analysis was performed to analyze various decoding parameters. While decoding parameters were generally well matched to the observed signals, several potential decoding improvements were identified. Overall, these results demonstrate the feasibility of epidural ECoG BCIs, highlight the importance of neural adaptation for BCI control, and quantify various metrics of a current ECoG BCI system to drive further studies

Next-generation optical access networks based on Orthogonal Frequency Division Multiplexing

Orthogonal Frequency Division Multiplexing (OFDM) is a robust modulation and multiplexing format which is at the base of many present communication standards. The interest of the OFDM application in optical fiber deployments is quite recent. As the next generation of Passive Optical Networks (NG-PONs) is envisioned, targeting greater capacity and user counts, the limitations of TDMA (Time Division Multiplexing Access) approaches to meet the expected increase in requirements becomes evident and therefore new technologies are being explored. Optical OFDMA is an emerging technology which can be a promising candidate. The main goal of this Master Thesis is to study the problem of users multiplexing in access networks, using OFDM as a technology to transmit the user information data. This work has focused in the uplink study of the network, because it is the most challenging part of the network to design. The studies have been conducted both in a theoretical way and also by simulating the targeted environments by means of a fiber optics transmission simulation tool. Virtual Photonics Integrated (VPI) is the software selected for the simulations. This tool is specially designed to simulate optical transmission system environments. The analysis of the Optical Beat Interference, which is a critical impairment in optical carrier multiplexing schemes, is the most important part of the user multiplexing study