The effect of spectral filters on reading speed and accuracy following stroke

Purpose - The aim of the study was to determine the effect of optimal spectral filters on reading performance following stroke. Methods - Seventeen stroke subjects, aged 43-85, were considered with an age-matched Control Group (n = 17). Subjects undertook the Wilkins Rate of Reading Test on three occasions: (i) using an optimally selected spectral filter; (ii) subjects were randomly assigned to two groups: Group 1 used an optimal filter, whereas Group 2 used a grey filter, for two-weeks. The grey filter had similar photopic reflectance to the optimal filters, intended as a surrogate for a placebo; (iii) the groups were crossed over with Group 1 using a grey filter and Group 2 given an optimal filter, for two weeks, before undertaking the task once more. An increase in reading speed of >5% was considered clinically relevant. Results - Initial use of a spectral filter in the stroke cohort, increased reading speed by ~8%, almost halving error scores, findings not replicated in controls. Prolonged use of an optimal spectral filter increased reading speed by >9% for stroke subjects; errors more than halved. When the same subjects switched to using a grey filter, reading speed reduced by ~4%. A second group of stroke subjects used a grey filter first; reading speed decreased by ~3% but increased by ~4% with an optimal filter, with error scores almost halving. Conclusions - The present study has shown that spectral filters can immediately improve reading speed and accuracy following stroke, whereas prolonged use does not increase these benefits significantly. © 2013 Spanish General Council of Optometry.

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

Optimal design of AC EMI filters with damping networks and effect on the systems power factor

The cutoff frequencies of an EMI filter are normally given by the noise attenuation requirements the filter has to fulfill. In order to select the component values of the filter elements, i.e. inductances and capacitances, an additional design criterium is needed. In this paper the effect of the EMI filter input and output impedances are considered. The input impedance influences the filters effect on the system displacement power factor and the output impedance plays a key role in the system stability. The effect of filter element values, the number of filter stages as well as additional damping networks are considered and a design procedure is provided. For this analysis a two-port description of the input filters employing ABCD-parameters is used.

Design of electron band pass filters for electrically biased finite superlattices

We design optimal band pass filters for electrons in semiconductor heterostructures, under a uniform applied electric field. The inner cells are chosen to provide a desired transmission window. The outer cells are then designed to transform purely incoming or outgoing waves into Bloch states of the inner cells. The transfer matrix is interpreted as a conformal mapping in the complex plane, which allows us to write constraints on the outer cell parameters, from which physically useful values can be obtained.

The role of embolic protection devices during carotid stenting prior to cardiac surgery in asymptomatic patients: Empty filters?

Objectives: The purpose of this study was to analyze the debris captured in the distal protection filters used during carotid artery stenting (CAS). Background: CAS is an option available to high-risk patients requiring revascularization. Filters are suggested for optimal stroke prevention during CAS. Methods: From May 2005 to June 2007, filters from 59 asymptomatic patients who underwent CAS were collected and sent to a specialized laboratory for light-microscope and histological analysis. Peri- and postprocedural outcomes were assessed during 1-year follow-up. Results: On the basis of biomedical imaging of the filter debris, the captured material could not be identified as embolized particles from the carotid plaque. On histological analysis the debris consisted mainly of red blood cell aggregates and/ or platelets, occasionally accompanied by granulocytes. We found no consistent histological evidence of embolized particles originating from atherosclerotic plaques. Post-procedure, three neurological events were reported: two (3.4%) transient ischemic attacks (TIA) and one (1.7%) ipsilateral minor stroke. Conclusion: The filters used during CAS in asymptomatic patients planned for cardiac surgery often remained empty. These findings may be explained by assuming that asymptomatic patients feature a different atherosclerotic plaque composition or stabilization through antiplatelet medication. Larger, randomized trials are clearly warranted, especially in the asymptomatic population. © 2012 Wiley Periodicals, Inc.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Development of Compact Microwave Filters Using Microstrip Loop Resonators

Study of the characteristics of planar loop resonators and their use in the construction of filters at microwave frequencies are presented in this thesis.A detailed investigation of parameters affecting the strength of coupling and the resonant frequency are also carried out .Techniques for size reduction in bandstop and bandpass filters using planar loop resonators are developed.Different configurations of bandstop and bandpass filters using loop resonators are simulated and experimental results on optimal filter configurations are presented.

Design of electron band pass filters for electrically biased finite superlattices

We design optimal band pass filters for electrons in semiconductor heterostructures, under a uniform applied electric field. The inner cells are chosen to provide a desired transmission window. The outer cells are then designed to transform purely incoming or outgoing waves into Bloch states of the inner cells. The transfer matrix is interpreted as a conformal mapping in the complex plane, which allows us to write constraints on the outer cell parameters, from which physically useful values can be obtained.

Optimal Unsupervised Learning in Feedforward Neural Networks

We investigate the properties of feedforward neural networks trained with Hebbian learning algorithms. A new unsupervised algorithm is proposed which produces statistically uncorrelated outputs. The algorithm causes the weights of the network to converge to the eigenvectors of the input correlation with largest eigenvalues. The algorithm is closely related to the technique of Self-supervised Backpropagation, as well as other algorithms for unsupervised learning. Applications of the algorithm to texture processing, image coding, and stereo depth edge detection are given. We show that the algorithm can lead to the development of filters qualitatively similar to those found in primate visual cortex.

Infrared filters for space-flight focal plane array applications

Infrared filters and coatings have been employed on many sensing radiometer instruments to measure the thermal emission profiles and concentrations of certian chemical constituents found in planetary atmospheres. The High Resolution Dynamics Limb Sounder ( HIRDLS) is an example of the most recent developments in limb-viewing radiometry by employing a cooled focal plane detector array to provide simultaneous multi-channel monitoring of emission from gas and aerosols over an altitude range between 8 - 70 km. The use of spectrally selective cooled detectors in focal plane arrays has simplified the optical layout of radiometers, greatly reducing the number of components in the optical train. this has inevitably led to increased demands for the enviromnetal durability of the focal plane filters because of the need to cut sub-millimeter sizes, whilst maintaining an optimal spectral performance. Additionally the remaining refractive optical elements require antireflection coatings which must cover the entire spectral range of the focal plane array channels, in this case 6 to 18µm, with a minimum of reflection and absorption. This paper describes the optical layout and spectral design requirements for filteriong in the HIRDLS instrument, and reports progress on the manufacturing and testing of the sub-millimetre sized cooled filters. We also report on the spectral and environmental performance of prototype wideband antireflection coatings which satisfy the requirements above.

Spectral design and verification of HIRDLS filters and antireflection coatings using an integrated system performance approach

The HIRDLS instrument contains 21 spectral channels spanning a wavelength range from 6 to 18mm. For each of these channels the spectral bandwidth and position are isolated by an interference bandpass filter at 301K placed at an intermediate focal plane of the instrument. A second filter cooled to 65K positioned at the same wavelength but designed with a wider bandwidth is placed directly in front of each cooled detector element to reduce stray radiation from internally reflected in-band signals, and to improve the out-of-band blocking. This paper describes the process of determining the spectral requirements for the two bandpass filters and the antireflection coatings used on the lenses and dewar window of the instrument. This process uses a system throughput performance approach taking the instrument spectral specification as a target. It takes into account the spectral characteristics of the transmissive optical materials, the relative spectral response of the detectors, thermal emission from the instrument, and the predicted atmospheric signal to determine the radiance profile for each channel. Using this design approach an optimal design for the filters can be achieved, minimising the number of layers to improve the in-band transmission and to aid manufacture. The use of this design method also permits the instrument spectral performance to be verified using the measured response from manufactured components. The spectral calculations for an example channel are discussed, together with the spreadsheet calculation method. All the contributions made by the spectrally active components to the resulting instrument channel throughput are identified and presented.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

Optimal and robust modal control of a flexible structure using an active dynamic vibration absorber

This paper is concerned with feedback vibration control of a lightly damped flexible structure that has a large number of well-separated modes. A single active electrical dynamic absorber is used to reduce a particular single vibration mode selectively or multiple modes simultaneously. The absorber is realized electrically by feeding back the structural acceleration at one position to a collocated piezoceramic patch actuator via a controller consisting of one or several second order lowpass filters. A simple analytical method is presented to design a modal control filter that is optimal in that it maximally flattens the mobility frequency response of the target mode, as well as robust in that it works within a prescribed maximum control spillover of 2 dB at all frequencies. Experiments are conducted with a free-free beam to demonstrate its ability to control any single mode optimally and robustly. It is also shown that an active absorber with multiple such filters can effectively control multiple modes simultaneously.

On designing linear tunable high-Q OTA-C filters with low sensitivity

This paper discusses a design approach for a high-Q low-sensitivity OTA-C biquad bandpass section. An optimal relationship is established between transconductances defining the differencebeta - gamma in the Q-factor denominator, setting the Q-sensitivity to tuning voltages around unity. A 30-MHz filter was designed based on a 0.35 mum CMOS process and V-DD=3.3 V. A range of circuit simulation supports the theoretical analysis. Q-factor spans from 20.5 to 60, while ensuring filter stability along the tuning range. Although a triode-operating OTA is used, the procedure can be extended to other types of transconductor.

On designing linearly tunable high-Q OTA-C filters with low sensitivity

This paper discusses a design approach for a high-Q low-sensitivity OTA-C biquad bandpass section. An optimal relationship is established between transconductances defining the differenceβ - γ in the Q-factor denominator, setting the Q-sensitivity to tuning voltages around unity. A 30-MHz filter was designed based on a 0.35μn CMOS process and VDD=3.3V. A range of circuit simulation supports the theoretical analysis. Q-factor spans from 20.5 to 60, while ensuring filter stability along the tuning range. Although a Mode-operating OTA is used, the procedure can be extended to other types of transconductor.