In this paper, a recursive least squares algorithm is proposed for a class of nonlinear dual-rate systems. By using the missing-output estimation model, the unavailable outputs can be estimated. Then, the unknown para...
详细信息
In this paper, a recursive least squares algorithm is proposed for a class of nonlinear dual-rate systems. By using the missing-output estimation model, the unavailable outputs can be estimated. Then, the unknown parameters can be estimated from all the inputs and outputs. Compared with the polynomial transformation technique and the lifting technique, the unknown parameters can be estimated directly by using the missing-output estimation model, without increasing the number of parameters. The convergence analysis and the simulation results indicate that the proposed method is effective.
A new compact form of the sliding window recursiveleastsquares (SWRLS) algorithm, the I-SWRLS algorithm, is derived using an indefinite matrix. The resultant algorithm has a form similar to that of the traditional r...
详细信息
A new compact form of the sliding window recursiveleastsquares (SWRLS) algorithm, the I-SWRLS algorithm, is derived using an indefinite matrix. The resultant algorithm has a form similar to that of the traditional recursiveleastsquares (RLS) algorithm, and is more computationally efficient than the conventional SWRLS algorithm including two Riccati equations. Furthermore, a computationally reduced version of the I-SWRLS algorithm is developed utilizing a shift property of the correlation matrix of input data. The resulting fast algorithm reduces the computational complexity from O(N-2) to O(N) per iteration when the filter length (tap number) is N. but retains the same tracking performance as the original algorithm. This fast algorithm is much easier to implement than the existing SWC FTF algorithms.
In this study, a new parameter estimation method based on coupled leastsquares method for recursive estimation of time-varying parameters in multivariable systems is presented. The bi-loop matrix forgetting factor-ba...
详细信息
In this study, a new parameter estimation method based on coupled leastsquares method for recursive estimation of time-varying parameters in multivariable systems is presented. The bi-loop matrix forgetting factor-based coupled recursiveleastsquares method is employed for estimation of time-varying parameters in which the forgetting factor for each parameter is adjusted according to its variance. This means that the forgetting factors of slow-varying and fast-varying parameters are calculated according to their variances, automatically. The simulation results demonstrate the advantage of the proposed method for estimation of parameters with different variation rates (including slow-varying or fast-varying parameters) in comparison with ordinary coupled leastsquares method.
The application of a recursive least squares algorithm to adaptive infinite impulse response (IIR) filters is investigated in this paper. A global convergence of an adaptive IIR filter is developed. It is shown that t...
详细信息
ISBN:
(纸本)7505338900
The application of a recursive least squares algorithm to adaptive infinite impulse response (IIR) filters is investigated in this paper. A global convergence of an adaptive IIR filter is developed. It is shown that the noll solutions of the parameter error vector, filtered error and output error in the filter are asymptotically stable for a stable reference signal. The analysis proceeds with simple algebra, does not rely on the commonly used hyperstability, strictly passive machinery and lower bounded input. The simulation results are also included to demonstrate the behaviours of the filter.
To adapt to the sparsity of some sparse systems in system identification, a novel modified recursive least squares algorithm is proposed. This algorithm utilizes the output error to control the value of forgetting fac...
详细信息
ISBN:
(纸本)9780956715753
To adapt to the sparsity of some sparse systems in system identification, a novel modified recursive least squares algorithm is proposed. This algorithm utilizes the output error to control the value of forgetting factor, which deals with the contradiction between convergence rate and stationary misadjustment. In addition, through the introduction of zero attractor in parameters' iterations, the proposed algorithm improves the convergence rate of zero and near-zero parameters dominating sparse systems. The simulation results indicate that the algorithm proposed in this paper can effectively strengthen the accuracy of sparse system identification.
Modification of recursive least squares algorithm is presented for identification of linear time-varying systems. The basic idea is to divide the weighting vector into two part. One represents the main variation tende...
详细信息
ISBN:
(纸本)9781509009107
Modification of recursive least squares algorithm is presented for identification of linear time-varying systems. The basic idea is to divide the weighting vector into two part. One represents the main variation tendency of the time-varying parameters, while the other is a slowly varying vector. First the former is determined by a procedure based on the dependency of data, and then the remaining part is identified using recursive least squares algorithm with forgetting factor. The modified algorithm avoids the problems appeared in rapidly varying situations, with good tracking ability.
in EEC;Electroencephalogram signals Artifacts records are originated due to various factors as line interference, EOG (electro-Oculogram) and ECG (electrocardiogram). These noise sources upsurge the striving in analyz...
详细信息
ISBN:
(纸本)9781509000760
in EEC;Electroencephalogram signals Artifacts records are originated due to various factors as line interference, EOG (electro-Oculogram) and ECG (electrocardiogram). These noise sources upsurge the striving in analyzing the EEG and to procurement clinical information. Therefore, specific filters design is obligatory to diminution of such artifacts in EEG records. This research work anticipated an adaptive filtering method for eradicating ocular artifacts from EEG records by performing. M-th Order FIR Filtering on Adaptive RLS algorithm. In this paper, the method accuracy is estimated by utilizing virtual data quantitatively and equated with the precision of the time-domain regression method. The outcomes suggest that EEG channels are frequency dependent for transfer of ocular signal. The proposed adaptive filtering technique is more precise for denoising of EEG signals.
This paper introduces the methodology and procedures of identification of overall coefficient of heat transfer (U-factor) of building envelopes using recursive least squares algorithm and dynamic heat transfer data. A...
详细信息
ISBN:
(纸本)9783037851272
This paper introduces the methodology and procedures of identification of overall coefficient of heat transfer (U-factor) of building envelopes using recursive least squares algorithm and dynamic heat transfer data. Application this method to three types of typical to examine the correctness and feasibility of this method. The following conclusions can be obtained: 1) Identification of U-factor of building envelopes using recursive least squares algorithm is feasible for engineering purpose, the identified U-factor can be near to its real value;2)The testing periods can be much shorter than the steady testing;3)The identification error is associated with the thermal inertia. The error is larger as the thermal inertia of building envelope is large within the same testing circumstances.
The use of electrical machines in automotive traction systems is rapidly increasing. To ensure operational safety, the machine behavior is monitored to detect failures or aging effects. Besides other approaches, onlin...
详细信息
ISBN:
(纸本)9798350397420
The use of electrical machines in automotive traction systems is rapidly increasing. To ensure operational safety, the machine behavior is monitored to detect failures or aging effects. Besides other approaches, online parameter identification is suited for real-time observation of the machine condition during operation. Two of the most established online parameter identification algorithms are the recursiveleastsquares and the extended Kalman filter algorithm. In existing approaches the algorithms identify the absolute parameter values. In this paper the used identification models are modified to directly identify the parameter deviation related to the reference values. This results in an additional advantage in identifying operational parameter changes because nonlinear behavior is provided by the respective parameter reference. The performance of the proposed algorithms to monitor different electrical parameter changes is compared using an extended analytical induction machine model.
In this article, we describe an innovative non-invasive method of Fetal Phonocardiography (fPCG) using fiber-optic sensors and adaptive algorithm for the measurement of fetal heart rate (fHR). Conventional PCG is base...
详细信息
ISBN:
(纸本)9781510613454;9781510613447
In this article, we describe an innovative non-invasive method of Fetal Phonocardiography (fPCG) using fiber-optic sensors and adaptive algorithm for the measurement of fetal heart rate (fHR). Conventional PCG is based on a noninvasive scanning of acoustic signals by means of a microphone placed on the thorax. As for fPCG, the microphone is placed on the maternal abdomen. Our solution is based on patent pending non-invasive scanning of acoustic signals by means of a fiber-optic interferometer. Fiber-optic sensors are resistant to technical artifacts such as electromagnetic interferences (EMI), thus they can be used in situations where it is impossible to use conventional EFM methods, e.g. during Magnetic Resonance Imaging (MRI) examination or in case of delivery in water. The adaptive evaluation system is based on recursiveleastsquares (RLS) algorithm. Based on real measurements provided on five volunteers with their written consent, we created a simplified dynamic signal model of a distribution of heartbeat sounds (HS) through the human body. Our created model allows us to verification of the proposed adaptive system RLS algorithm. The functionality of the proposed non-invasive adaptive system was verified by objective parameters such as Sensitivity (S+) and Signal to Noise Ratio (SNR).
暂无评论