Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Signal-to-noise ratio of the MEG signal after preprocessing

Background Magnetoencephalography (MEG) provides a direct measure of brain activity with high combined spatiotemporal resolution. Preprocessing is necessary to reduce contributions from environmental interference and biological noise. New method The effect on the signal-to-noise ratio of different preprocessing techniques is evaluated. The signal-to-noise ratio (SNR) was defined as the ratio between the mean signal amplitude (evoked field) and the standard error of the mean over trials. Results Recordings from 26 subjects obtained during and event-related visual paradigm with an Elekta MEG scanner were employed. Two methods were considered as first-step noise reduction: Signal Space Separation and temporal Signal Space Separation, which decompose the signal into components with origin inside and outside the head. Both algorithm increased the SNR by approximately 100%. Epoch-based methods, aimed at identifying and rejecting epochs containing eye blinks, muscular artifacts and sensor jumps provided an SNR improvement of 5–10%. Decomposition methods evaluated were independent component analysis (ICA) and second-order blind identification (SOBI). The increase in SNR was of about 36% with ICA and 33% with SOBI. Comparison with existing methods No previous systematic evaluation of the effect of the typical preprocessing steps in the SNR of the MEG signal has been performed. Conclusions The application of either SSS or tSSS is mandatory in Elekta systems. No significant differences were found between the two. While epoch-based methods have been routinely applied the less often considered decomposition methods were clearly superior and therefore their use seems advisable.

Noise resilient discrete-time cross-relation sensor characterisation

In-situ characterisation of thermocouple sensors is a challenging problem. Recently the authors presented a blind characterisation technique based on the cross-relation method of blind identification. The method allows in-situ identification of two thermocouple probes, each with a different dynamic response, using only sampled sensor measurement data. While the technique offers certain advantages over alternative methods, including low estimation variance and the ability to compensate for noise induced bias, the robustness of the method is limited by the multimodal nature of the cost function. In this paper, a normalisation term is proposed which improves the convexity of
the cost function. Further, a normalisation and bias compensation hybrid approach is presented that exploits the advantages of both normalisation and bias compensation. It is found that the optimum of the hybrid cost function is less biased and more stable than when only normalisation is applied. All results were verified by simulation.

Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs

In this paper we propose a novel fast random search clustering (RSC) algorithm for mixing matrix identification in multiple input multiple output (MIMO) linear blind inverse problems with sparse inputs. The proposed approach is based on the clustering of the observations around the directions given by the columns of the mixing matrix that occurs typically for sparse inputs. Exploiting this fact, the RSC algorithm proceeds by parameterizing the mixing matrix using hyperspherical coordinates, randomly selecting candidate basis vectors (i.e. clustering directions) from the observations, and accepting or rejecting them according to a binary hypothesis test based on the Neyman–Pearson criterion. The RSC algorithm is not tailored to any specific distribution for the sources, can deal with an arbitrary number of inputs and outputs (thus solving the difficult under-determined problem), and is applicable to both instantaneous and convolutive mixtures. Extensive simulations for synthetic and real data with different number of inputs and outputs, data size, sparsity factors of the inputs and signal to noise ratios confirm the good performance of the proposed approach under moderate/high signal to noise ratios. RESUMEN. Método de separación ciega de fuentes para señales dispersas basado en la identificación de la matriz de mezcla mediante técnicas de "clustering" aleatorio.

A high-resolution genetic map of the familial Mediterranean fever candidate region allows identification of haplotype-sharing among ethnic groups

Familial Mediterranean fever (FMF) is a recessive disorder of inflammation caused by mutations in a gene (designated MEFV) on chromosome 16p13.3, We have recently constructed a 1-Mb cosmid contig that includes the FMF critical region. Here we show genotype data for 12 markers from our physical map, including 5 newly identified microsatellites, in FMF families. Intrafamilial recombinations placed MEFV in the similar to 285 kb between D16S468/D16S3070 and D16S3376. We observed significant linkage disequilibrium in the North African Jewish population, and historical recombinants in the founder haplotype placed MEFV between D16S3082 and D16S3373 (similar to 200 kb). In smaller panels of Iraqi Jewish, Arab, and Armenian families, there were significant allelic associations only for D16S3370 and D16S2617 among the Armenians. A sizable minority of Iraqi Jewish and Armenian carrier chromosomes appeared to be derived from the North African Jewish ancestral haplotype. We observed a unique FMF haplotype common to Iraqi Jews, Arabs, and Armenians and two other haplotypes restricted to either the Iraqi Jewish or the Armenian population. These data support the view that a few major mutations account for a large percentage of the cases of FMF and suggest that same of these mutations arose before the affected Middle Eastern populations diverged from one another. (C) 1997 Academic Press.

Efficacy of vitamin D3 as add-on therapy in patients with relapsing-remitting multiple sclerosis receiving subcutaneous interferon β-1a: a Phase II, multicenter, double-blind, randomized, placebo-controlled trial.

Recent studies have demonstrated the immunomodulatory properties of vitamin D, and vitamin D deficiency may be a risk factor for the development of MS. The risk of developing MS has, in fact, been associated with rising latitudes, past exposure to sun and serum vitamin D status. Serum 25-hydroxyvitamin D [25(OH)D] levels have also been associated with relapses and disability progression. The identification of risk factors, such as vitamin D deficiency, in MS may provide an opportunity to improve current treatment strategies, through combination therapy with established MS treatments. Accordingly, vitamin D may play a role in MS therapy. Small clinical studies of vitamin D supplementation in patients with MS have reported positive immunomodulatory effects, reduced relapse rates and a reduction in the number of gadolinium-enhancing lesions. However, large randomized clinical trials of vitamin D supplementation in patients with MS are lacking. SOLAR (Supplementation of VigantOL(®) oil versus placebo as Add-on in patients with relapsing-remitting multiple sclerosis receiving Rebif(®) treatment) is a 96-week, three-arm, multicenter, double-blind, randomized, placebo-controlled, Phase II trial (NCT01285401). SOLAR will evaluate the efficacy of vitamin D(3) as add-on therapy to subcutaneous interferon beta-1a in patients with RRMS. Recruitment began in February 2011 and is aimed to take place over 1 calendar year due to the potential influence of seasonal differences in 25(OH)D levels.

Perfusion-CT guided intravenous thrombolysis in patients with unknown-onset stroke: a randomized, double-blind, placebo-controlled, pilot feasibility trial.

INTRODUCTION: Patients with unknown stroke onset are generally excluded from acute recanalisation treatments. We designed a pilot study to assess feasibility of a trial of perfusion computed tomography (PCT)-guided thrombolysis in patients with ischemic tissue at risk of infarction and unknown stroke onset. METHODS: Patients with a supratentorial stroke of unknown onset in the middle cerebral artery territory and significant volume of at-risk tissue on PCT were randomized to intravenous thrombolysis with alteplase (0.9 mg/kg) or placebo. Feasibility endpoints were randomization and blinded treatment of patients within 2 h after hospital arrival, and the correct application (estimation) of the perfusion imaging criteria. RESULTS: At baseline, there was a trend towards older age [69.5 (57-78) vs. 49 (44-78) years] in the thrombolysis group (n = 6) compared to placebo (n = 6). Regarding feasibility, hospital arrival to treatment delay was above the allowed 2 h in three patients (25%). There were two protocol violations (17%) regarding PCT, both underestimating the predicted infarct in patients randomized in the placebo group. No symptomatic hemorrhage or death occurred during the first 7 days. Three of the four (75%) and one of the five (20%) patients were recanalized in the thrombolysis and placebo group respectively. The volume of non-infarcted at-risk tissue was 84 (44-206) cm(3) in the treatment arm and 29 (8-105) cm(3) in the placebo arm. CONCLUSIONS: This pilot study shows that a randomized PCT-guided thrombolysis trial in patients with stroke of unknown onset may be feasible if issues such as treatment delays and reliable identification of tissue at risk of infarction tissue are resolved. Safety and efficiency of such an approach need to be established.

Testing advances in molecular discrimination among Chinook salmon life histories: evidence from a blind test.

The application of DNA-based markers toward the task of discriminating among alternate salmon runs has evolved in accordance with ongoing genomic developments and increasingly has enabled resolution of which genetic markers associate with important life-history differences. Accurate and efficient identification of the most likely origin for salmon encountered during ocean fisheries, or at salvage from fresh water diversion and monitoring facilities, has far-reaching consequences for improving measures for management, restoration and conservation. Near-real-time provision of high-resolution identity information enables prompt response to changes in encounter rates. We thus continue to develop new tools to provide the greatest statistical power for run identification. As a proof of concept for genetic identification improvements, we conducted simulation and blind tests for 623 known-origin Chinook salmon (Oncorhynchus tshawytscha) to compare and contrast the accuracy of different population sampling baselines and microsatellite loci panels. This test included 35 microsatellite loci (1266 alleles), some known to be associated with specific coding regions of functional significance, such as the circadian rhythm cryptochrome genes, and others not known to be associated with any functional importance. The identification of fall run with unprecedented accuracy was demonstrated. Overall, the top performing panel and baseline (HMSC21) were predicted to have a success rate of 98%, but the blind-test success rate was 84%. Findings for bias or non-bias are discussed to target primary areas for further research and resolution.

Treatment rationale and study design for a phase III, double-blind, placebo-controlled study of maintenance pemetrexed plus best supportive care versus best supportive care immediately following induction treatment with pemetrexed plus cisplatin for advanced nonsquamous non-small cell lung cancer.

BACKGROUND: To improve the efficacy of first-line therapy for advanced non-small cell lung cancer (NSCLC), additional maintenance chemotherapy may be given after initial induction chemotherapy in patients who did not progress during the initial treatment, rather than waiting for disease progression to administer second-line treatment. Maintenance therapy may consist of an agent that either was or was not present in the induction regimen. The antifolate pemetrexed is efficacious in combination with cisplatin for first-line treatment of advanced NSCLC and has shown efficacy as a maintenance agent in studies in which it was not included in the induction regimen. We designed a phase III study to determine if pemetrexed maintenance therapy improves progression-free survival (PFS) and overall survival (OS) after cisplatin/pemetrexed induction therapy in patients with advanced nonsquamous NSCLC. Furthermore, since evidence suggests expression levels of thymidylate synthase, the primary target of pemetrexed, may be associated with responsiveness to pemetrexed, translational research will address whether thymidylate synthase expression correlates with efficacy outcomes of pemetrexed. METHODS/DESIGN: Approximately 900 patients will receive four cycles of induction chemotherapy consisting of pemetrexed (500 mg/m2) and cisplatin (75 mg/m2) on day 1 of a 21-day cycle. Patients with an Eastern Cooperative Oncology Group performance status of 0 or 1 who have not progressed during induction therapy will randomly receive (in a 2:1 ratio) one of two double-blind maintenance regimens: pemetrexed (500 mg/m2 on day 1 of a 21-day cycle) plus best supportive care (BSC) or placebo plus BSC. The primary objective is to compare PFS between treatment arms. Secondary objectives include a fully powered analysis of OS, objective tumor response rate, patient-reported outcomes, resource utilization, and toxicity. Tumor specimens for translational research will be obtained from consenting patients before induction treatment, with a second biopsy performed in eligible patients following the induction phase. DISCUSSION: Although using a drug as maintenance therapy that was not used in the induction regimen exposes patients to an agent with a different mechanism of action, evidence suggests that continued use of an agent present in the induction regimen as maintenance therapy enables the identification of patients most likely to benefit from maintenance treatment.

The identification of two Trypanosoma cruzi I genotypes from domestic and sylvatic transmission cycles in Colombia based on a single polymerase chain reaction amplification of the spliced-leader intergenic region

A single polymerase chain reaction (PCR) reaction targeting the spliced-leader intergenic region of Trypanosoma cruzi I was standardised by amplifying a 231 bp fragment in domestic (TcIDOM) strains or clones and 450 and 550 bp fragments in sylvatic strains or clones. This reaction was validated using 44 blind coded samples and 184 non-coded T. cruzi I clones isolated from sylvatic triatomines and the correspondence between the amplified fragments and their domestic or sylvatic origin was determined. Six of the nine strains isolated from acute cases suspected of oral infection had the sylvatic T. cruzi I profile. These results confirmed that the sylvatic T. cruzi I genotype is linked to cases of oral Chagas disease in Colombia. We therefore propose the use of this novel PCR reaction in strains or clones previously characterised as T. cruziI to distinguish TcIDOMfrom sylvatic genotypes in studies of transmission dynamics, including the verification of population selection within hosts or detection of the frequency of mixed infections by both T. cruzi I genotypes in Colombia.

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Randomised controlled trials of homeopathy in hyperactive children: treatment procedure leads to an unconventional study design. Experience with open-label homeopathic treatment preceding the Swiss ADHD placebo controlled, randomised, double-blind, cross-over trial

BACKGROUND: Treatment of patients with attention deficit hyperactivity disorder (ADHD) with homeopathy is difficult. The Swiss randomised, placebo controlled, cross-over trial in ADHD patients (Swiss ADHD trial) was designed with an open-label screening phase prior to the randomised controlled phase. During the screening phase, the response of each child to successive homeopathic medications was observed until the optimal medication was identified. Only children who reached a predefined level of improvement participated in the randomised, cross-over phase. Although the randomised phase revealed a significant beneficial effect of homeopathy, the cross-over caused a strong carryover effect diminishing the apparent difference between placebo and verum treatment. METHODS: This retrospective analysis explores the screening phase data with respect to the risk of failure to demonstrate a specific effect of a randomised controlled trial (RCT) with randomisation at the start of the treatment. RESULTS: During the screening phase, 84% (70/83) of the children responded to treatment and reached eligibility for the randomised trial after a median time of 5 months (range 1-18), with a median of 3 different medications (range 1-9). Thirteen children (16%) did not reach eligibility. Five months after treatment start, the difference in Conners Global Index (CGI) rating between responders and non-responders became highly significant (p = 0.0006). Improvement in CGI was much greater following the identification of the optimal medication than in the preceding suboptimal treatment period (p < 0.0001). CONCLUSIONS: Because of the necessity of identifying an optimal medication before response to treatment can be expected, randomisation at the start of treatment in an RCT of homeopathy in ADHD children has a high risk of failure to demonstrate a specific treatment effect, if the observation time is shorter than 12 months.

Linking genome and proteome by mass spectrometry: Large-scale identification of yeast proteins from two dimensional gels

The function of many of the uncharacterized open reading frames discovered by genomic sequencing can be determined at the level of expressed gene products, the proteome. However, identifying the cognate gene from minute amounts of protein has been one of the major problems in molecular biology. Using yeast as an example, we demonstrate here that mass spectrometric protein identification is a general solution to this problem given a completely sequenced genome. As a first screen, our strategy uses automated laser desorption ionization mass spectrometry of the peptide mixtures produced by in-gel tryptic digestion of a protein. Up to 90% of proteins are identified by searching sequence data bases by lists of peptide masses obtained with high accuracy. The remaining proteins are identified by partially sequencing several peptides of the unseparated mixture by nanoelectrospray tandem mass spectrometry followed by data base searching with multiple peptide sequence tags. In blind trials, the method led to unambiguous identification in all cases. In the largest individual protein identification project to date, a total of 150 gel spots—many of them at subpicomole amounts—were successfully analyzed, greatly enlarging a yeast two-dimensional gel data base. More than 32 proteins were novel and matched to previously uncharacterized open reading frames in the yeast genome. This study establishes that mass spectrometry provides the required throughput, the certainty of identification, and the general applicability to serve as the method of choice to connect genome and proteome.