On the eigenfilter design method and its applications: a tutorial

The eigenfilter method for digital filter design involves the computation of filter coefficients as the eigenvector of an appropriate Hermitian matrix. Because of its low complexity as compared to other methods as well as its ability to incorporate various time and frequency-domain constraints easily, the eigenfilter method has been found to be very useful. In this paper, we present a review of the eigenfilter design method for a wide variety of filters, including linear-phase finite impulse response (FIR) filters, nonlinear-phase FIR filters, all-pass infinite impulse response (IIR) filters, arbitrary response IIR filters, and multidimensional filters. Also, we focus on applications of the eigenfilter method in multistage filter design, spectral/spacial beamforming, and in the design of channel-shortening equalizers for communications applications

Representational organization of novel task sets during proactive encoding

Recent multivariate analyses of brain data have boosted our understanding of the organizational principles that shape neural coding. However, most of this progress has focused on perceptual visual regions (Connolly et al., 2012), whereas far less is known about the organization of more abstract, action-oriented representations. In this study, we focused on humans{\textquoteright} remarkable ability to turn novel instructions into actions. While previous research shows that instruction encoding is tightly linked to proactive activations in fronto-parietal brain regions, little is known about the structure that orchestrates such anticipatory representation. We collected fMRI data while participants (both males and females) followed novel complex verbal rules that varied across control-related variables (integrating within/across stimuli dimensions, response complexity, target category) and reward expectations. Using Representational Similarity Analysis (Kriegeskorte et al., 2008) we explored where in the brain these variables explained the organization of novel task encoding, and whether motivation modulated these representational spaces. Instruction representations in the lateral prefrontal cortex were structured by the three control-related variables, while intraparietal sulcus encoded response complexity and the fusiform gyrus and precuneus organized its activity according to the relevant stimulus category. Reward exerted a general effect, increasing the representational similarity among different instructions, which was robustly correlated with behavioral improvements. Overall, our results highlight the flexibility of proactive task encoding, governed by distinct representational organizations in specific brain regions. They also stress the variability of motivation-control interactions, which appear to be highly dependent on task attributes such as complexity or novelty.SIGNIFICANCE STATEMENTIn comparison with other primates, humans display a remarkable success in novel task contexts thanks to our ability to transform instructions into effective actions. This skill is associated with proactive task-set reconfigurations in fronto-parietal cortices. It remains yet unknown, however, how the brain encodes in anticipation the flexible, rich repertoire of novel tasks that we can achieve. Here we explored cognitive control and motivation-related variables that might orchestrate the representational space for novel instructions. Our results showed that different dimensions become relevant for task prospective encoding depending on the brain region, and that the lateral prefrontal cortex simultaneously organized task representations following different control-related variables. Motivation exerted a general modulation upon this process, diminishing rather than increasing distances among instruction representations

Scene-based nonuniformity correction with video sequences and registration

We describe a new, to our knowledge, scene-based nonuniformity correction algorithm for array detectors. The algorithm relies on the ability to register a sequence of observed frames in the presence of the fixed-pattern noise caused by pixel-to-pixel nonuniformity. In low-to-moderate levels of nonuniformity, sufficiently accurate registration may be possible with standard scene-based registration techniques. If the registration is accurate, and motion exists between the frames, then groups of independent detectors can be identified that observe the same irradiance (or true scene value). These detector outputs are averaged to generate estimates of the true scene values. With these scene estimates, and the corresponding observed values through a given detector, a curve-fitting procedure is used to estimate the individual detector response parameters. These can then be used to correct for detector nonuniformity. The strength of the algorithm lies in its simplicity and low computational complexity. Experimental results, to illustrate the performance of the algorithm, include the use of visible-range imagery with simulated nonuniformity and infrared imagery with real nonuniformity

Ultrafast Dynamics of Vibrational Symmetry Breaking in a Charge-ordered Nickelate

The ability to probe symmetry breaking transitions on their natural time scales is one of the key challenges in nonequilibrium physics. Stripe ordering represents an intriguing type of broken symmetry, where complex interactions result in atomic-scale lines of charge and spin density. Although phonon anomalies and periodic distortions attest the importance of electron-phonon coupling in the formation of stripe phases, a direct time-domain view of vibrational symmetry breaking is lacking. We report experiments that track the transient multi-THz response of the model stripe compound La$_{1.75}$Sr$_{0.25}$NiO$_{4}$, yielding novel insight into its electronic and structural dynamics following an ultrafast optical quench. We find that although electronic carriers are immediately delocalized, the crystal symmetry remains initially frozen - as witnessed by time-delayed suppression of zone-folded Ni-O bending modes acting as a fingerprint of lattice symmetry. Longitudinal and transverse vibrations react with different speeds, indicating a strong directionality and an important role of polar interactions. The hidden complexity of electronic and structural coupling during stripe melting and formation, captured here within a single terahertz spectrum, opens new paths to understanding symmetry breaking dynamics in solids.Comment: 21 pages, 4 figures; updated version with journal re

Understanding student experience in the age of personalised study

Moves in higher education to provide personalised learning for students increase the importance of gaining and maintaining an understanding of the student experience. For some institutions, this increase in complexity may stretch current systems and data structures. The complexity is amplified where multiple start dates are offered to improve the personalisation of study. The Open University, OU, has over the years, continued to develop its Supported Open Learning, SOL, methods and as an institution is now prioritising Personalised Open Learning, POL. This increases the importance of accessible detailed pathway information. We describe the development of one possible approach intended to provide greater understanding of the student experience for staff interpreting progress data. Another outcome of personalisation is the fragmentation of student cohorts, as individuals each make their own study choices while progressing towards their study goal. A relatively straightforward programme of study can lead to 64 different study routes creating a further challenge for staff in understanding the differing student experiences. We show how this can be represented in a simple data structure that allows powerful queries. Our approach uses a multi-model database, with graphical capabilities. By creating this structure in the ArangoDB environment it was possible to readily test it with 150,000 records and query it using graphical queries in the native AQL language. The early response from faculty colleagues is very positive. They appreciate the graphical output and the ability to straightforwardly answer their questions on whether students experience greater success on one study route rather than another. We are therefore continuing to develop this model to support a qualification review for summer 2018. In our presentation we will describe the challenge and illustrate an approach we are taking: giving examples of the queries we are using and the kinds of data the system outputs

Development and mathematical analysis of a modular CNG valve : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering, Mechatronics, at Massey University

With the rising cost of oil and uncertainty of supply, there has never been a greater opportunity to offer an alternative fuel into the automotive market than at this present time. Compressed natural gas (CNG) and liquid petroleum gas (LPG) are popular alternatives, producing less green house gasses after the combustion process that add to the raising global warming concern. With high performance fuel injected state of the art engines used in the majority of the late model vehicles, the problem when running on CNG or LPG is poor control of the air/fuel ratio throughout the engine's speed and load range using the conventional zero pressure regulator and mixer combination gas conversion equipment used previously for carburetted engines. This problem is completely eliminated with gas injection system. The Harrison CNG Electronic Gas injection System control valve is a linear proportional valve. Testing on the valve has found that the response is linear under all operating conditions; however the valve exhibits occasional instances of hysteresis. Due to this unfortunate characteristic further analysis is required, in the form of a mathematical analysis, to determine the exact causes of this problem. Another point of concern is the complexity of the valve, due to the many moving parts, this results in high production costs and increased reliability concerns. This masters project will include the mathematical analysis of the current Harrison CNG Electronic Gas injection system, further testing and refinement. The objective is to produce a modular system that can be retrofitted to any make of vehicle. Research will be directed in the development of mathematical equations to analyse valve operation for improvement of operation, to increase performance the valve will be redesigned to reduce complexity and ready it for production. The valve will be tested on a variety of vehicles from a 2 litre sedan to a 5.8 litre diesel engine that has been converted to operate on CNG, to prove the versatility of the valve and its ability to tailor the engine torque curve to that required for the vehicles unique operating requirements

The Host Gatekeeper: Using the Flagellar Pathway to Understand Symbiont Host Adaptation

The acquisition of microbial partners is a strategy used by a diverse group of arthropods to overcome ecological barriers that might normally make certain niches uninhabitable. The unique phylogenetic opportunities attainable from the natural experiment of the Sodalis-allied clade allow for better understanding of how molecular structures evolve through time. Here, we focus on the evolution of the flagellar synthesis pathway, due to its complexity and ability to diverge in response to ecological pressures. We used this molecular pathway and natural experiment to show that normal evolutionary outcomes associated with symbiosis (i.e., genome reduction) do not explain the predicted conservation of the flagella genes or lack thereof within ancestral nodes