System identification from noisy measurements by using instrumental variables and subspace fitting

This paper considers the estimation of the parameters of a linear discrete-time system from noise-perturbed input and output measurements. The conditions imposed on the system are fairly general. In particular, the input and output noises are allowed to be auto-correlated and they may be cross-correlated as well. The proposed method makes use of an instrumental variable (IV)-vector to produce a covariance matrix that is pre- and postmultiplied by some prechosen weights. The singular vectors of the so-obtained matrix possess complete information on the system parameters. A weighted subspace fitting (WSF) method is then applied to the aforementioned singular vectors to consistently estimate the parameters of the system. The IV-WSF technique suggested herein is noniterative and easy to implement, and has a small computational burden. The asymptotic distribution of its estimation errors is derived and the result is used to motivate the choice of the weighting matrix in the WSF step and also to predict the estimation accuracy. Numerical examples are included to illustrate the performance achievable by the method.This work has been supported by the Swedish Research Council of Engineering Sciences under contract 93-669 and by the Göran Gustafsson Foundation.     

MODE-type algorithm for estimating damped, undamped, or explosive modes

We propose a new algorithm for estimating the parameters of damped, undamped, or explosive sinusoidal signals. The algorithm resembles the MODE algorithm, which is commonly used for direction of arrival estimation in the array signal processing field. It is derived as a natural approximation to an asymptotically (high-SNR) optimal parameter estimator and has excellent statistical accuracy. Nevertheless, it is computationally simple and easy to implement. Numerical examples are included to illustrate the performance of the proposed method.This work has been supported by the Swedish Research Council for Engineering Sciences (TFR).     

On LP-MUSIC

Studies the consistency properties of a method recently proposed for temporal or spatial frequency estimation from noisy data. The method in question is a MUSIC technique that makes use of a linear prediction algorithm to determine the signal subspace. It is shown that the signal subspace determined by the subject linear prediction-MUSIC (LP-MUSIC) algorithm can collapse in certain scenarios and. Hence, that the LP-MUSIC frequency estimates are not always consistent. The difficulties LP-MUSIC may encounter in some cases are illustrated by means of numerical examples     

Detection tests for array processing in unknown correlated noisefields

This paper introduces two eigenvalue-based rules for estimating the number of signals impinging on an array of sensors along with a spatially correlated noise field. The first rule, called S, is derived under the assumption that the noise spatial covariance is block diagonal or banded. The assumption underlying the second detection rule, named T, is that the temporal correlation of the noise has a shorter length than that of the signals. In both cases, a matrix is built from the array output data covariances, the smallest eigenvalue of which is equal to zero under the hypothesis that the source number is overestimated. The sample distribution of the aforementioned smallest eigenvalue is derived and used to formulate the detection rules S and T. Both these rules are computationally quite simple. Additionally, they can be used with a noncalibrated array. The paper includes numerical examples that lend empirical support to the theoretical findings and illustrate the kind of performance that can be achieved by using the S and T detection rules     

Combined instrumental variable and subspace fitting approach toparameter estimation of noisy input-output systems

The paper considers the problem of estimating the parameters of linear discrete-time systems from noise-corrupted input-output measurements, under fairly general conditions: the output and input noises may be auto-correlated and they may be cross-correlated as well. By using the instrumental-variable (IV) principle a covariance matrix is obtained, the singular vectors of which bear complete information on the parameters of the system under study. A weighted subspace fitting (WSF) procedure is then employed on the sample singular vectors to derive estimates of the parameters of the system. The combined IV-WSF method proposed in the present paper is noniterative and simple to use. Its large-sample statistical performance is analyzed in detail and the theoretical results so obtained are used to predict the behavior of the method in samples with practical lengths. Several numerical examples are included to show the agreement between the theoretically predicted and the empirically observed performances     

Expression of the Aryl Hydrocarbon Receptor in Growth Plate Cartilage and the Impact of Its Local Modulation on Longitudinal Bone Growth

Although dioxin has been reported to impair bone growth in both humans and animals, the underlying mechanisms have not been clarified. We conducted this study to rule out if dioxin may directly target the growth plate, via local modulation of the aryl hydrocarbon receptor (AhR). Initial studies in rare tissue samples of the human growth plate confirmed that the AhR protein is widely expressed in growth plate cartilage. To explore the local role of the AhR, mechanistic studies were performed in a well-established model of cultured fetal rat metatarsal bones. The longitudinal growth of these bones was monitored while being exposed to AhR modulators. The AhR agonist, 2,3,7,8-tetrachlorodibenzo-p-dioxin, did not affect bone growth at any concentrations tested (1 pM–10 nM). In contrast, the AhR antagonist, alpha-naphthoflavone, suppressed bone growth and increased chondrocyte apoptosis, although only at a high, potentially cytotoxic concentration (50 µM). We conclude that although the AhR is widely expressed in the growth plate, bone growth is not modulated when locally activated, and therefore, dioxin-induced growth failure is likely mediated through systemic rather than local actions.     

A class of perfect block codes for the binary channel associated with differentially encoded PSK signals with coherent detection (Corresp.)

A class of perfect block codes are found for the binary channel associated with differentially encoded phase shift keying signals with coherent detection (DCPSK). The codes are shown to correct all double adjacent errors and single errors in the first and last word positions. Such codes are found for which the number of available different syndromes equals the number of most probable channel errors. A construction algorithm is given for this class of codes. Computer search results for shortened codes are presented.     

A structured channel estimator for maximum likelihood sequencedetection in multipath fading channels

This paper describes a channel estimator using known prior information about the transmit and receive filters, it is shown that the composite channel lies in a certain subspace obtained from the impulse responses of these filters. A structured linear channel model is then developed that is linearly parameterized by an unknown vector. To illustrate the potential usefulness of such an approach, the estimated structured channel is used in a multisensor and oversampled maximum likelihood sequence estimation (MLSE) receiver. We also present expressions on the pairwise error probability for the MLSE receiver based on the structured channel model. Using these results, we investigate the phenomenon of error flooring     

A structured channel estimator for maximum-likelihood sequencedetection

This letter describes a channel estimator using known prior information about the transmit and receive filters. It is shown that the composite channel lies in the subspace of the transmit and receive filter impulse responses. A structured linear channel model is then developed that is linearly parametrized by an unknown vector. To illustrate the potential usefulness of such an approach, the estimated structured channel is used in a multisensor and oversampled maximum-likelihood sequence estimation (MLSE) receiver