Search results for: ERROR ESTIMATION
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DOP and Pseudorange Error Estimation in Mobile GNSS Systems for Android OS Applications
PublicationIn the near past, GNSS (Global Navigation Satellite Systems) were only offered for a narrow group of recipients. Nowadays, thanks to mobile devices, they are available to anyone and everywhere. Personal navigation, searching for POI (Point of Interest), etc., had become a basic essential activity. Thanks to the widespread and availability of smartphones each user can obtain information considering his or her location even in an...
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DOP and Pseudorange Error Estimation in Urban Environments for Mobile Android GNSS Applications
PublicationJust a couple of years ago, GNSS (Global Navigation Satellite Systems) were available only for a narrow group of users. Currently, with the outbreak of mobile devices, they are accessible to anyone and everywhere. Urban navigation or searching for POIs (Points of Interest) had become an everyday activity. With the availability of consumer electronics and wireless technologies, each user can obtain information considering his or...
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Minimum mean square error estimation of speech short-term predictor parameters under noisy conditions
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Bounding approach to parameter estimation without priori knowledge on model structure error.
PublicationArtykuł przedstawia estymację parametrów modelu ARMA (Autoregresive moving average) metodą zbiorów ograniczonych. Założono brak wiedzy na temat ograniczeń na błąd struktury modelu lub, że wiedza ta jest bardzo konserwatywna. W celu redukcji tego konserwatyzmu, zaproponowano koncepcje modelu punktowo-parametrycznego. W podejściu tym zakłada się istnienie zbioru parametrów modelu oraz błędu struktury odpowiadających każdej z trajektorii...
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Bounding approach to parameter estimation without prior knowledge on modeling error and application to quality modeling in drinking water distribution systems
PublicationW artykule rozważana jest estymacja parametrów modelu autoregresji z ruchoma średnią i sygnałem wejściowym (ARMAX) z wykorzystaniem przedziałowego modelu błędu. Zakłada się, że granice błędu struktury modelu są nieznane, bądź znane, ale bardzo konserwatywne. Dla zmniejszenia tego konserwatyzmu proponowane jest idea modeli punktowo-parametrycznych, w której występują zbiory parametrów i błędu modelu odpowiadające wszystkim wejściom....
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Underwater Navigation Ssystem Based on Doppler Shift – Measurements and Error Estimations
PublicationA new acoustic navigation system was developed to determine the position and speed of moving underwater objects such as divers and underwater vehicles. The path of an object and its speed were determined by the Doppler shifts of acoustic signals emitted by a transmitter placed on the object and received by four hydrophones installed at the periphery of the monitored body of water. The position and speed measurements were affected...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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New results on estimation bandwidth adaptation
PublicationThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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Respiratory Rate Estimation Based on Detected Mask Area in Thermal Images
PublicationThe popularity of non-contact methods of measuring vital signs, particularly respiratory rate, has increased during the SARS-COV-2 pandemic. Breathing parameters can be estimated by analysis of temperature changes observed in thermal images of nostrils or mouth regions. However, wearing virus-protection face masks prevents direct detection of such face regions. In this work, we propose to use an automatic mask detection approach...
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On the Usefulness of the Generalised Additive Model for Mean Path Loss Estimation in Body Area Networks
PublicationIn this article, the usefulness of the Generalised Additive Model for mean path loss estimation in Body Area Networks is investigated. The research concerns a narrow-band indoor off-body network operating at 2.45 GHz, being based on measurements performed with four different users. The mean path loss is modelled as a sum of four components that depend on path length, antenna orientation angle, absolute difference between transmitting...
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Estimation of Average Speed of Road Vehicles by Sound Intensity Analysis
PublicationConstant monitoring of road traffic is important part of modern smart city systems. The proposed method estimates average speed of road vehicles in the observation period, using a passive acoustic vector sensor. Speed estimation based on sound intensity analysis is a novel approach to the described problem. Sound intensity in two orthogonal axes is measured with a sensor placed alongside the road. Position of the apparent sound...
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A new method of wind farm active power curve estimation based on statistical approach
PublicationThe purpose of this paper is to solve the wind farm active power estimation problem, introducing the method which is based on a statistical approach and robust fitting. The proposed algorithm uses a statistical approach and compared to existing ones- includes a wind direction as well as the influence of turbine start-up procedure on the estimation. The results show that additional estimation inputs i.e. the wind direction and the...
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A Novel Approach of Using Selected Unconventional Geodesic Methods of Estimation on VTS Areas
PublicationThe Vessel Traffic Service (VTS) systems belong to the fundamental tools used in ensuring a high level of safety across sea basins with heavy traffic, where the presence of navigational hazards poses a great risk of collision or a ship running aground. In order to determine the mutual location of ships, VTS systems obtain information from different facilities, such as coastal radar stations, AIS, and vision systems. Fixing a ship’s...
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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublicationNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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On autoregressive spectrum estimation using the model averaging technique
PublicationThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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Akaike's final prediction error criterion revisited
PublicationWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Estimation of respiration rate using an accelerometer and thermal camera in eGlasses
PublicationRespiration rate is a very important vital sign. Different methods of respiration rate measurement or estimation have been developed. However, especially interesting are those that enable remote and unobtrusive monitoring. In this study, we investigated the use of smart glasses for the estimation of respiration rate especially useful for indoors applications. Two methods were analyzed. The first one is based on measurements of...