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PubMed2005

Signal processing strategies that improve performance and understanding of the quantitative ultrasound SPECTRAL FIT algorithm.

Quantifying the size of the tissue microstructure using the backscattered power spectrum has had limited success due to frequency-dependent attenuation along the propagation path, thus masking the frequency dependence of the scatterer size. Previously, the SPECTRAL FIT algorithm was developed to solve for total attenuation and scatterer size simultaneously [Bigelow et al., J. Acoust. Soc. Am. 117, 1431-1439 (2005)]. Herein, the outcomes from signal processing strategies on the SPECTRAL FIT algorithm are investigated. The signal processing methods can be grouped into two categories, viz., methods that improve the performance of the algorithm and methods that provide insight. The methods that improve the performance include compensating for the windowing function used to gate the time-domain signal, averaging the spectra in the normal frequency domain rather than the log domain to improve the precision of the scatterer size and attenuation estimates, improving the selection of the usable frequency range for the SPECTRAL FIT algorithm, and improving the compensation for electronic noise. The methods that provide insight demonstrate that the anomalous rapid fluctuations of the backscattered power spectrum do not affect the SPECTRAL FIT algorithm, and accurate attenuation estimates can be obtained even when the correct scatterer geometry (i.e., form factor) is not known.

Algorithms↗

PubMed2005

Subspace algorithms for noise reduction in cochlear implants.

A single-channel algorithm is proposed for noise reduction in cochlear implants. The proposed algorithm is based on subspace principles and projects the noisy speech vector onto "signal" and "noise" subspaces. An estimate of the clean signal is made by retaining only the components in the signal subspace. The performance of the subspace reduction algorithm is evaluated using 14 subjects wearing the Clarion device. Results indicated that the subspace algorithm produced significant improvements in sentence recognition scores compared to the subjects' daily strategy, at least in stationary noise. Further work is needed to extend the subspace algorithm to nonstationary noise environments.

Adult↗

PubMed1995

Objective speech quality assessment and the RPE-LTP coding algorithm in different noise and language conditions.

The formulation of reliable signal processing algorithms for speech coding and synthesis require the selection of a prior criterion of performance. Though coding efficiency (bits/second) or computational requirements can be used, a final performance measure must always include speech quality. In this paper, three objective speech quality measures are considered with respect to quality assessment for American English, noisy American English, and noise-free versions of seven languages. The purpose is to determine whether objective quality measures can be used to quantify changes in quality for a given voice coding method, with a known subjective performance level, as background noise or language conditions are changed. The speech coding algorithm chosen is regular-pulse excitation with long-term prediction (RPE-LTP), which has been chosen as the standard voice compression algorithm for the European Digital Mobile Radio system. Three areas are considered for objective quality assessment which include: (i) vocoder performance for American English in a noise-free environment, (ii) speech quality variation for three additive background noise sources, and (iii) noise-free performance for seven languages which include English, Japanese, Finnish, German, Hindi, Spanish, and French. It is suggested that although existing objective quality measures will never replace subjective testing, they can be a useful means of assessing changes in performance, identifying areas for improvement in algorithm design, and augmenting subjective quality tests for voice coding/compression algorithms in noise-free, noisy, and/or non-English applications.

Adult↗

PubMed1998

An active noise control algorithm for controlling multiple sinusoids.

The filtered-x LMS algorithm and its modified versions have been successfully applied in suppressing acoustic noise such as single and multiple tones and broadband random noise. This paper presents an adaptive algorithm based on the filtered-x LMS algorithm which may be applied in attenuating tonal acoustic noise. In the proposed method, the weights of the adaptive filter and estimation of the phase shift due to the acoustic path from a loudspeaker to a microphone are computed simultaneously for optimal control. The algorithm possesses advantages over other filtered-x LMS approaches in three aspects: (1) each frequency component is processed separately using an adaptive filter with two coefficients, (2) the convergence parameter for each sinusoid can be selected independently, and (3) the computational load can be reduced by eliminating the convolution process required to obtain the filtered reference signal. Simulation results for a single-input/single-output (SISO) environment demonstrate that the proposed method is robust to the changes of the acoustic path between the actuator and the microphone and outperforms the filtered-x LMS algorithm in simplicity and convergence speed.

Acoustics↗

PubMed1993

Genetic algorithms: principles of natural selection applied to computation.

A genetic algorithm is a form of evolution that occurs on a computer. Genetic algorithms are a search method that can be used for both solving problems and modeling evolutionary systems. With various mapping techniques and an appropriate measure of fitness, a genetic algorithm can be tailored to evolve a solution for many types of problems, including optimization of a function of determination of the proper order of a sequence. Mathematical analysis has begun to explain how genetic algorithms work and how best to use them. Recently, genetic algorithms have been used to model several natural evolutionary systems, including immune systems.

Algorithms↗

PubMed1995

Algorithm for use of nucleic acid probes for identifying Mycobacterium tuberculosis from BACTEC 12B bottles.

Nucleic acid probes (Gen-Probe, San Diego, Calif.) can be used to identify mycobacteria in BACTEC 12B broth cultures prior to detection of growth on solid media. We developed an algorithm that can be used to make an initial choice of a probe (either Mycobacterium tuberculosis complex [MTB] or M. avium complex [MAC]) for use in testing respiratory specimens. The algorithm was based on both the fluorochrome smear result of the concentrated specimen and the time from inoculation until the BACTEC 12B broth culture is flagged (growth index 10) as presumptively positive. The MTB probe is used first for all 4+ smear specimens, 3+ smear specimens positive in 5 days, 2+ and 1+ smear specimens positive in 7 days, and smear-negative specimens positive in 11 days. The MAC probe is used for all other specimens. The algorithm is used when other information about the culture (e.g., previous positive cultures and colonial morphology of growth on solid media) is unknown. Use of the algorithm to probe 102 respiratory BACTEC 12B broth cultures (35 with MTB; 1 with MTB, MAC, and M. gordonae; 47 with MAC; and 19 with other mycobacterial species) from 1 September through 30 November 1992 resulted in the initial use of the MTB probe for 35 (97%) of the cultures positive for MTB and the use of the MAC probe for 35 (73%) of the cultures positive for MAC. Use of the algorithm aided in the efficient use of laboratory resources without delaying the time to identification of MTB isolates.

Algorithms↗

PubMed1998

Clinical evaluation of scanning laser polarimetry: I. Intraoperator reproducibility and design of a blood vessel removal algorithm.

AIMS: To evaluate the reproducibility of the retardation values (change in polarisation) obtained with the scanning-laser polarimeter in a series of normal subjects and glaucoma patients. To improve the analysis of the raw data by devising and evaluating a blood vessel removal algorithm. METHODS: Scanning laser polarimetry was performed on 10 normal subjects and 10 glaucoma patients. A series of six images was obtained from each eye. The normal subjects were re-imaged 3 months after their initial assessment. The retardation values obtained from each eye were analysed using the authors' own methods, including the use of an algorithm to remove blood vessels from the polar profiles. The reproducibility of these measurements and the performance of the blood vessel removal algorithm were assessed. RESULTS: The "individual point" coefficient of variation was approximately 12.5% for normal subjects and 17.0% for glaucoma patients. The "integral" coefficient of variation for these groups was approximately 5.5% and 9.5% respectively. The reproducibility of the measurements did not improve with an increased number of measurements. There was no difference in the reproducibility of the measurements in normal subjects over time. The blood vessel removal algorithm improved the reproducibility of the measurements when the shape of the profile was assessed. CONCLUSION: The intraoperator reproducibility of retardation values obtained with the scanning laser polarimeter is satisfactory for its use as a clinical tool. The use of a blood vessel removal algorithm improves the reproducibility of the measurements and also assists the clinician in the interpretation of the polar profiles. Furthermore, it allows the construction of normal database polar profiles, thereby enabling the identification, location and quantification of retinal nerve fibre layer damage in an "at risk" individual's polar profile.

Algorithms↗

PubMed1996

A simple algorithm to predict the development of radiological erosions in patients with early rheumatoid arthritis: prospective cohort study.

OBJECTIVE: To produce a practical algorithm to predict which patients with early rheumatoid arthritis will develop radiological erosions. DESIGN: Primary care based prospective cohort study. SETTING: All general practices in the Norwich Health Authority, Norfolk. SUBJECTS: 175 patients notified to the Norfolk Arthritis Register were visited by a metrologist soon after they had presented to their general practitioners with inflammatory polyarthritis, and again after a further 12 months. All the patients satisfied the American Rheumatism Association's 1987 criteria for rheumatoid arthritis and were seen by a metrologist within six months of the onset of symptoms. The study population was randomly split into a prediction sample (n = 105) for generating the algorithm and a validation sample (n = 70) for testing it. MAIN OUTCOME MEASURES: Predictor variables measured at baseline included rheumatoid factor status, swelling of specific joint areas, duration of morning stiffness, nodules, disability score, age, sex, and disease duration when the patient first presented. The outcome variable was the presence of radiological erosions in the hands or feet, or both, after 12 months. RESULTS: A simple algorithm based on a combination of three variables--a positive rheumatoid factor test, swelling of at least two large joints, and a disease duration of more than three months--was best able to predict erosions. When the accuracy of this algorithm was tested with the validation sample, the erosion status of 79% of patients was predicted correctly. CONCLUSIONS: A simple algorithm based on three easily measured items of information can predict which patients are at high risk and which are at low risk of developing radiological erosions.

Adult↗

PubMed2006

Prospective validation of a current algorithm including bedside US performed by emergency physicians for patients with acute flank pain suspected for renal colic.

OBJECTIVE: The purpose of this study was to validate an algorithm recommended by current literature for the patients with acute flank pain and evaluate the validity of bedside ultrasonography (US) performed by emergency physicians (EP) as a part of this algorithm. MATERIALS AND METHODS: This prospective validation study was carried out over a 5 month period in a tertiary care hospital adult emergency department (ED) with annual attendance of 55,000. Adult patients presenting to the ED with unilateral acute flank pain during the study period were enrolled into the study consecutively. Oral consent was obtained after the protocol was briefly explained to the patient and before the administration of analgesia. A protocol form was recorded for each patient enrolled into the study, and patients were followed up under the guidance of a previously designated algorithm in the ED. Data were analysed with SPSS software. The chi2 test was used to compare the dichotomised data of patients, diagnosed with and without stones, and to select the significant parameters to be used in the logistic regression. RESULTS: Of the 227 patients enrolled, 176 were proven to have urinary tract stones. There were 122 patients discharged from ED without further investigation except urinalysis and bedside US. Of these 122 directly discharged patients, 99 had a urinary stone, and the others did not have a life threatening disorder. Four of the 227 patients were admitted to the hospital. The remaining 51 patients did not have stones detected, and their pain subsided. Having a previous history of stones, radiation of pain to the groin, accompanying nausea, and detection of pelvicalyceal dilatation using bedside US performed by the EPs were found to be the most significant parameters in determining urinary stones in logistic regression analysis. Sensitivity and specificity of these parameters were: previous history of stones 59% and 66%, radiating pain to the groin 68% and 49%, nausea 71% and 51%, and detection of pelvicalyceal dilatation by bedside US 81% and 37%. CONCLUSION: Bedside US performed by EPs could be used safely in the evaluation of patients with acute flank pain as a part of a clinical algorithm. Previous history of urinary stones, radiation of pain to the groin, accompanying nausea. and detection of pelvicalyceal dilatation are major parameters and symptoms of urinary stone disease, and could be used in the algorithms.

Acute Disease↗

PubMed1998

Predicting operative risk for coronary artery surgery in the United Kingdom: a comparison of various risk prediction algorithms.

OBJECTIVE: To compare the ability of four risk models to predict operative mortality after coronary artery bypass graft surgery (CABG) in the United Kingdom. DESIGN: Prospective study. SETTING: Two cardiothoracic centres in the United Kingdom. SUBJECTS: 1774 patients having CABG. MAIN OUTCOME MEASURES: Risk factors were recorded for all patients, along with in-hospital mortality. Predicted mortality was derived from the American Society of Thoracic Surgeons (STS) risk program, Ontario Province risk score (PACCN), Parsonnet score, and the UK Society of Cardiothoracic Surgeons risk algorithm. RESULTS: There were significant differences (p < 0.05) between the British and American populations from which the STS risk algorithm was derived with respect to most variables. The observed mortality in the British population was 3.7% (65 of 1774). The mean predicted mortality by STS score, PACCN, Parsonnet score, and UK algorithms were 1.1%, 1.6%, 4.6%, and 4.7% respectively. The overall predictive ability of the models as measured by the area under the receiver operating characteristic curve were 0.64, 0.60, 0.73, and 0.75, respectively. CONCLUSIONS: There are differences between the British and American populations for CABG and the North American algorithms are not useful for predicting mortality in the United Kingdom. The UK Society of Cardiothoracic Surgeons algorithm is the best of the models tested but still only has limited predictive ability. Great care must be exercised when using methods of this type for comparisons of units and surgeons.

Aged↗

PubMed2005

Trauma: development of a sub-algorithm.

BACKGROUND: Anaesthetists are regularly involved in the management of patients who have suffered trauma. Acute physiological derangements can occur at any time after the original injury, with life threatening sequelae. These problems may be complex in nature and evolve rapidly, often with an obscure aetiology, so a systematic approach to them is essential. OBJECTIVES: To examine the role of a previously described core algorithm "COVER ABCD-A SWIFT CHECK" supplemented by a specific sub-algorithm for trauma, in the management of anaesthesia involving trauma cases. METHODS: The potential performance of a structured approach for each of the trauma incidents among the first 4000 incidents reported to the Australian Incident Monitoring Study (AIMS) was compared with the actual performance as reported by the anaesthetists involved. RESULTS: There were 38 relevant reports relating to trauma in the first 4000 reports to AIMS. In 39% of these there was "emergency corner cutting", although in the majority the urgency was thought to have been more perceived than real. The previously described "core" crisis management algorithm for crises during general anaesthesia was an effective means of discovering (82%), diagnosing (68%), and correcting (66%) the majority of trauma incidents. However a sub-algorithm specific for the traumatised patient was required for unusual, obscure, or complex presentations. CONCLUSION: Although the small numbers preclude validation of the sub-algorithm, it would have successfully managed all the trauma cases reported to AIMS.

Algorithms↗

PubMed2001

A fast and convergent stochastic MLP learning algorithm.

We propose a stochastic learning algorithm for multilayer perceptrons of linear-threshold function units, which theoretically converges with probability one and experimentally exhibits 100% convergence rate and remarkable speed on parity and classification problems with typical generalization accuracy. For learning the n bit parity function with n hidden units, the algorithm converged on all the trials we tested (n=2 to 12) after 5.8 x 4.1(n) presentations for 0.23 x 4.0(n-6) seconds on a 533MHz Alpha 21164A chip on average, which is five to ten times faster than Levenberg-Marquardt algorithm with restarts. For a medium size classification problem known as Thyroid in UCI repository, the algorithm is faster in speed and comparative in generalization accuracy than the standard backpropagation and Levenberg-Marquardt algorithms.

Algorithms↗

PubMed1993

The ClusNet algorithm and time series prediction.

This paper describes a novel neural network architecture named ClusNet. This network is designed to study the trade-offs between the simplicity of instance-based methods and the accuracy of the more computational intensive learning methods. The features that make this network different from existing learning algorithms are outlined. A simple proof of convergence of the ClusNet algorithm is given. Experimental results showing the convergence of the algorithm on a specific problem is also presented. In this paper, ClusNet is applied to predict the temporal continuation of the Mackey-Glass chaotic time series. A comparison between the results obtained with ClusNet and other neural network algorithms is made. For example, ClusNet requires one-tenth the computing resources of the instance-based local linear method for this application while achieving comparable accuracy in this task. The sensitivity of ClusNet prediction accuracies on specific clustering algorithms is examined for an application. The simplicity and fast convergence of ClusNet makes it ideal as a rapid prototyping tool for applications where on-line learning is required.

Algorithms↗

PubMed2006

Algorithms for challenging motif problems.

Pevzner and Sze(19) have introduced the Planted (l,d)-Motif Problem to find similar patterns (motifs) in sequences which represent the promoter regions of co-regulated genes, where l is the length of the motif and d is the maximum Hamming distance around the similar patterns. Many algorithms have been developed to solve this motif problem. However, these algorithms either have long running times or do not guarantee the motif can be found. In this paper, we introduce new algorithms to solve this motif problem. Our algorithms can find motifs in reasonable time for not only the challenging (9, 2), (11, 3), (15, 5)-motif problems but for even longer motifs, say (20, 7), (30, 11) and (40, 15), which have never been seriously attempted by other researchers because of the large time and space required. Besides, our algorithms can be extended to find more complicated motifs structure called cis-regulatory modules (CRM).

Algorithms↗

PubMed1998

On the use of neural network techniques to analyze sleep EEG data. Third communication: robustification of the classificator by applying an algorithm obtained from 9 different networks.

This is the third communication on the use of neural network techniques to classify sleep stages. In our first communication we presented the algorithms and the selection of the feature space and its reduction by using evolutionary and genetic procedures. In our second communication we trained the evolutionary optimized networks on the basis of multiple subject data in context with some smoothing algorithms in analogy of Rechtschaffen and Kales (RK). In this third communication we could demonstrate that the robustness concerning individual specific features of automatically generated sleep profiles could be reasonably improved by an additional modification of the procedure used by SASCIA (Sleep Analysis System to Challenge Innovative Artificial Networks). The outputs of nine different networks that were created by the data of 9 different subjects were used simultaneously for classification. The medians of the values obtained in each output measure were selected for the allocation to a sleep stage. The fitness criteria of 16 automatically generated sleep profiles showed reasonable concordance with the expert profile. Even though in single cases the concordance between conventional RK classifications and automatically generated profiles were a few percentages lower, the average correct classification of the 12 classified subjects improved substantially, thus proving that the classifier is more robust against individuum-specific variability. Despite the fact that the expert generally employs three channels (EEG, EMG and EOG), at least to build up sleep profiles, the SASCIA system was able to produce profiles on the basis of only one EEG channel with 80% concordance and a correlation coefficient of 0.86. The feature selections were performed by genetic algorithms and the topologies of the networks were optimized by evolutionary algorithms. This algorithm will now be used for larger sample forward classification.

Algorithms↗

PubMed2000

Nonholonomic orthogonal learning algorithms for blind source separation.

Independent component analysis or blind source separation extracts independent signals from their linear mixtures without assuming prior knowledge of their mixing coefficients. It is known that the independent signals in the observed mixtures can be successfully extracted except for their order and scales. In order to resolve the indeterminacy of scales, most learning algorithms impose some constraints on the magnitudes of the recovered signals. However, when the source signals are nonstationary and their average magnitudes change rapidly, the constraints force a rapid change in the magnitude of the separating matrix. This is the case with most applications (e.g., speech sounds, electroencephalogram signals). It is known that this causes numerical instability in some cases. In order to resolve this difficulty, this article introduces new nonholonomic constraints in the learning algorithm. This is motivated by the geometrical consideration that the directions of change in the separating matrix should be orthogonal to the equivalence class of separating matrices due to the scaling indeterminacy. These constraints are proved to be nonholonomic, so that the proposed algorithm is able to adapt to rapid or intermittent changes in the magnitudes of the source signals. The proposed algorithm works well even when the number of the sources is overestimated, whereas the existent algorithms do not (assuming the sensor noise is negligibly small), because they amplify the null components not included in the sources. Computer simulations confirm this desirable property.

Algorithms↗

PubMed2000

On-line EM algorithm for the normalized gaussian network.

A normalized gaussian network (NGnet) (Moody & Darken, 1989) is a network of local linear regression units. The model softly partitions the input space by normalized gaussian functions, and each local unit linearly approximates the output within the partition. In this article, we propose a new on-line EMalgorithm for the NGnet, which is derived from the batch EMalgorithm (Xu, Jordan, &Hinton 1995), by introducing a discount factor. We show that the on-line EM algorithm is equivalent to the batch EM algorithm if a specific scheduling of the discount factor is employed. In addition, we show that the on-line EM algorithm can be considered as a stochastic approximation method to find the maximum likelihood estimator. A new regularization method is proposed in order to deal with a singular input distribution. In order to manage dynamic environments, where the input-output distribution of data changes over time, unit manipulation mechanisms such as unit production, unit deletion, and unit division are also introduced based on probabilistic interpretation. Experimental results show that our approach is suitable for function approximation problems in dynamic environments. We also apply our on-line EM algorithm to robot dynamics problems and compare our algorithm with the mixtures-of-experts family.

Algorithms↗

PubMed2003

Linear geometric ICA: fundamentals and algorithms.

Geometric algorithms for linear independent component analysis (ICA) have recently received some attention due to their pictorial description and their relative ease of implementation. The geometric approach to ICA was proposed first by Puntonet and Prieto (1995). We will reconsider geometric ICA in a theoretic framework showing that fixed points of geometric ICA fulfill a geometric convergence condition (GCC), which the mixed images of the unit vectors satisfy too. This leads to a conjecture claiming that in the nongaussian unimodal symmetric case, there is only one stable fixed point, implying the uniqueness of geometric ICA after convergence. Guided by the principles of ordinary geometric ICA, we then present a new approach to linear geometric ICA based on histograms observing a considerable improvement in separation quality of different distributions and a sizable reduction in computational cost, by a factor of 100, compared to the ordinary geometric approach. Furthermore, we explore the accuracy of the algorithm depending on the number of samples and the choice of the mixing matrix, and compare geometric algorithms with classical ICA algorithms, namely, Extended Infomax and FastICA. Finally, we discuss the problem of high-dimensional data sets within the realm of geometrical ICA algorithms.

Algorithms↗