Cerebral Synchrony Assessment Tutorial: A General Review on Cerebral Signals' Synchronization Estimation Concepts and Methods

The human brain is ultimately responsible for all thoughts and movements that the body produces. This allows humans to successfully interact with their environment. If the brain is not functioning properly many abilities of human can be damaged. The goal of cerebral signal analysis is to learn about brain function. The idea that distinct areas of the brain are responsible for specific tasks, the functional segregation, is a key aspect of brain function. Functional integration is an important feature of brain function, it is the concordance of multiple segregated brain areas to produce a unified response. There is an amplified feedback mechanism in the brain called reentry which requires specific timing relations. This specific timing requires neurons within an assembly to synchronize their firing rates. This has led to increased interest and use of phase variables, particularly their synchronization, to measure connectivity in cerebral signals. Herein, we propose a comprehensive review on concepts and methods previously presented for assessing cerebral synchrony, with focus on phase synchronization, as a tool for brain connectivity evaluation

Optimization of a 50 MHz Frequency Modulated Continuous Wave radar system for the study of auroral E-region coherent backscatter

A 50 MHz Frequency Modulated Continuous Wave (FMCW) radar system, developed at the University of Saskatchewan to provide improved spatial and temporal resolution measurements of auroral E-region plasma processes, introduces ambiguous spectral information, due to spectral ghosting, for scattering events in which multiple radar echoes are detected. This thesis identifies two Linearly Frequency Modulated (LFM) radar waveforms used by the FMCW system as the source of the ghosting. An analysis procedure designed to counteract the spectral ghosting problem is developed but is not an ideal solution, and therefore replacement of the LFM waveforms is recommended. A detailed investigation of alternative radar waveforms using the Ambiguity Function and Ambiguity Diagram techniques is performed. A frequency coded continuous wave radar waveform based on a composite Costas sequence is proposed as a successor to the LFM waveforms. The composite Costas radar waveform will conserve the spatial and temporal resolutions extended by the LFM waveforms and preclude any spectral ghosting. Implementing the proposed radar waveform and avoiding receiver saturation issues with the mono-static FMCW radar system in which both the transmitting and receiving antenna arrays are simultaneously and continuously active and geographically co-located is also discussed. In addition to this, two 50 MHz backscatter events are presented in this thesis to demonstrate the effectiveness of the FMCW system, notwithstanding the spectral ghosting complication. The first event from November 21, 2009 is identified as a Type 1 instability and the second from September 13, 2009 is identified as a Type 2 instability which lasted for ~ 16 minutes. Linear plasma fluid theory is used to provide a brief interpretation of both scattering events

4D Frequency Analysis of Computational Cameras for Depth of Field Extension

Depth of field (DOF), the range of scene depths that appear sharp in a photograph, poses a fundamental tradeoff in photography---wide apertures are important to reduce imaging noise, but they also increase defocus blur. Recent advances in computational imaging modify the acquisition process to extend the DOF through deconvolution. Because deconvolution quality is a tight function of the frequency power spectrum of the defocus kernel, designs with high spectra are desirable. In this paper we study how to design effective extended-DOF systems, and show an upper bound on the maximal power spectrum that can be achieved. We analyze defocus kernels in the 4D light field space and show that in the frequency domain, only a low-dimensional 3D manifold contributes to focus. Thus, to maximize the defocus spectrum, imaging systems should concentrate their limited energy on this manifold. We review several computational imaging systems and show either that they spend energy outside the focal manifold or do not achieve a high spectrum over the DOF. Guided by this analysis we introduce the lattice-focal lens, which concentrates energy at the low-dimensional focal manifold and achieves a higher power spectrum than previous designs. We have built a prototype lattice-focal lens and present extended depth of field results

Instantaneous Power Spectrum

The estimation of time varying spectra is a complicated one. The use of classical techniques coupled with the local stationarity assumption is met with only moderate success. Of the many time frequency distribution functions used in the signal analysis, none present fully satisfactory spectra. The performance of the spectrogram, Instantaneous Power Spectra (IPS) the Wigner-Ville Distribution (WD) and various aspects of the Rihaczek distribution (RD) for a variety of signal nonstationarities are compared. WD has the most narrow main-lobes but suffers from spectral cross-terms. IPS, the real part of the RD consistently shows a broadened main-lobe without cross-terms. The squared magnitude of the RD places sharp peaks along the crest of the main-lobe and is otherwise very similar to IPS. The imaginary part of the RD shows a sensitivity to discontinuous frequency changes i.e., frequency shift keying.http://archive.org/details/instantaneouspow1094537553Lieutenant, Unuted States NavyApproved for public release; distribution is unlimited

SNR degradation in GNSS-R measurements under the effects of radio-frequency interference

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Radio-frequency interference (RFI) is a serious threat for systems working with low power signals such as those coming from the global navigation satellite systems (GNSS). The spectral separation coefficient (SSC) is the standard figure of merit to evaluate the signal-to-noise ratio (SNR) degradation due to the RFI. However, an in-depth assessment in the field of GNSS-Reflectometry (GNSS-R) has not been performed yet, and particularly, about which is the influence of the RFI on the so-called delay-Doppler map (DDM). This paper develops a model that evaluates the contribution of intra-/inter-GNSS and external RFI effects to the degradation of the SNR in the DDM for both conventional and interferometric GNSS-R techniques. Moreover, a generalized SSC is defined to account for the effects of nonstationary RFI signals. The results show that highly directive antennas are necessary to avoid interference from other GNSS satellites, whereas mitigation techniques are essential to keep GNSS-R instruments working under external RFI degradation.Peer ReviewedPostprint (author's final draft

Time-frequency methods for coherent spectroscopy

Time-frequency decomposition techniques, borrowed from the signal-processing field, have been adapted and applied to the analysis of 2D oscillating signals. While the Fourier-analysis techniques available so far are able to interpret the information content of the oscillating signal only in terms of its frequency components, the time-frequency transforms (TFT) proposed in this work can instead provide simultaneously frequency and time resolution, unveiling the dynamics of the relevant beating components, and supplying a valuable help in their interpretation. In order to fully exploit the potentiality of this method, several TFTs have been tested in the analysis of sample 2D data. Possible artifacts and sources of misinterpretation have been identified and discussed