Circuits, Systems and Signal Processing最新文献

The current paper investigates the issue of designing adaptive robust subspace detectors in Gaussian noise whose covariance matrix is unknown. The original problem is revised by importing a fictitious signal with a given structure within the signal-plus-noise hypothesis to collect leakage signals around the subspace, thus increasing the credibility of this hypothesis in situations involving mismatch. To solve the issue described above, we utilize the generalized likelihood ratio test, Rao, Wald, Gradient, and Durbin tests to derive five adaptive subspace detectors. Both theoretical proofs and Monte Carlo simulation results suggest that these proposed detectors possess the constant false alarm rate properties. Numerical examples reveal the effectiveness of these proposed detectors and show their varying degrees of robustness under mismatch scenarios.

The Hilbert transformation for generating the analytic signal or signal envelope is widely used in modern communication receivers, in radar and sonar systems. It introduces a (90^{circ }) phase shift of the input signal. Since the impulse response of the ideal Hilbert transformer is non-causal, it must be approximated by an FIR or IIR filter. This paper shows results of novel algorithms for designing broadband digital IIR Hilbert transformers and its implementation. The designs employ Galerkin or collocation techniques. The transfer function of the Hilbert transformer is a rational polynomial of low order and exhibits approximately linear phase. The filters match the (90^{circ }) phase shift requirement of Hilbert transformers almost perfectly and exhibit approximately constant group delay in the passband. The achieved image rejection ratio is typically larger than 50 dB. The quantization of the filter coefficients is realized by a Canonical Signed Digit (CSD) representation, reducing the hardware resources compared with two’s complement. The resulting filters are multiplier-less, which is crucial for high-speed signal processing and low power consumption. The design techniques and the CSD representation are realized in a MATLAB toolbox. The filters were moreover implemented in VHDL and SystemC. Additionally, a MATLAB tool for automatically generating a VHDL package containing the filter parameters has been implemented.

Digital communication systems usually suffer from two factors: inter-symbol interference and impulsive noise. To improve the performance of communication receivers, this paper proposes a good solution to a linear blind equalizer. Firstly, a new lower-order statistic with a lower influence of impulsive noise is constructed based on a nonlinear function. Secondly, an unconstrained optimization problem is formulated by minimizing the mean square error related to the new lower-order statistic, and a new equalization algorithm is derived to effectively compensate for the inter-symbol interference. Thirdly, to further enhance the robustness of the proposed algorithm, the iterative formula of the proposed algorithm is handled by normalizing samples. Finally, numerical simulation results demonstrate that the proposed algorithm achieves better performance under Gaussian and impulsive noise.

In the fault-tolerant control tasks of nonlinear systems, unmeasurable states, time delay and actuator faults are considered to be the main factors hindering effective controller design and tracking performance improvement. To solve these problems, firstly, a state observer is established to estimate the unmeasurable of the system and the prescribed performance control based on error transformation is presented to maintain system efficiency and reliability. Secondly, the problem of controller design caused by input delay is effectively solved by constructing an auxiliary tracking error and auxiliary system and combining with the well-designed Lyapunov-Krasovskii functionals. Thirdly, the newly employed damping term in the intermediate control law is utilized to compensate for the possibly unlimited number of faults. Then, it is proved that all signals are semi-global practical finite-time stable based on the backstepping technique. Meanwhile, the tracking error can converge to a specified range within finite time. Finally, comparative simulations are presented to demonstrate the effectiveness of the proposed method.

Powerline interference (PLI) more frequently affects the electrocardiogram (ECG) signal during the recording and acquisition. This paper proposes a unique method for suppressing the PLI in the ECG signal using an adaptive filter (AF) with a modified lightning search algorithm (MLSA). The MLSA approach automatically updates the filter coefficient weights to minimize the error between the noisy ECG signal and the filter output. The input signal of a filter is also optimized based on the error signal using MLSA. The proposed methodology's effectiveness is verified by adding PLI noise to the ECG records from the MIT-BIH arrhythmia database at different signal-to-noise ratios (SNRs). The potency of the proposed methodology is assessed by evaluation metrics, namely SNR improvement, mean square error (MSE), mean absolute error (MAE), percentage of root-mean-square difference (PRD), Huber loss (HL), and the correlation coefficient (CC). The results of the proposed methods outperform the existing techniques of empirical mode decomposition, variational mode decomposition with a non-local mean approach, empirical wavelet transform, variational mode decomposition with a variable notch filter, and an AF with the least mean square (LMS) approach in terms of evaluation metrics and visual observation.

In this study, teaching learning-based optimization algorithm (TLBO) has been explored in order abatement (OA) and controller design of the linear time-invariant (LTI) systems. Motivated by various optimization approaches available in the literature, with TLBO’s unique computational abilities like fast convergence, simple mathematical steps and gradient free approach, the study aims to determine the unknown coefficients of the abated system (AS) by minimizing the integral square error (ISE) between the higher order system (HOS) and the AS. The efficacy and supremacy of the suggested approach has been demonstrated using six distinct control systems of high order. In order to assess the performance of the proposed method, the obtained results are compared with HOS and lower order system already available in the literature. It reveals that the proposed AS maintains stability and the steady state conditions of the HOS. To further illustrate the practical application of TLBO, a 4th order system has been considered and a proportional-integral (PI) controller is designed using the proposed 2nd order AS.

This paper considers output-based adaptive event-triggered control of saturated system with the dynamic anti-windup compensator. An adaptive event-triggered condition with a time-varying threshold function is proposed, under which the system has better performance in saving communication resources. A dynamic anti-windup compensator is employed to overcome the potential performance degradation caused by input saturation. For the prescribed dynamic anti-windup compensator, an optimization problem is proposed for enlarging the domain of attraction. Moreover, if dynamic anti-windup compensator is not given in advance, co-design of the dynamic anti-windup compensator and adaptive event-triggered condition is developed. In addition, the Zeno behavior is excluded by calculating the minimum triggering time interval. Finally, the theoretical result is verified by numerical simulation.

Group delay processing of audio signals has been extensively studied in the last decade. In this paper, tonic estimation in Turkish makam music is addressed using modified group delay processing. Tonic is one of the stable pitches of the performance, which serves as the reference throughout the performance. The proposed methodology does not require metadata such as the melodic pitch values of the audio files for tonic estimation. Modified group delay functions (MODGD) computed from the flattened music spectrum of non-melodic segments are bin-wise summed to form a summary-modgdgram. The peak position in the tonic range of summary-modgdgram is mapped to the tonic pitch. Two corpora of the Turkish music tonic dataset, created by the CompMusic project group, are used to assess the system. The proposed methodology outperforms the baseline last note detection (LND) method, which uses pitch contour as a prerequisite for tonic estimation. The results show the potential of processing audio signals using the phase-based approach in tonic pitch estimation.

Spoken language change detection (LCD) refers to identifying the language transitions in a code-switched utterance. Similarly, identifying the speaker transitions in a multispeaker utterance is known as speaker change detection (SCD). Since tasks-wise both are similar, the architecture/framework developed for the SCD task may be suitable for the LCD task. Hence, the aim of the present work is to develop LCD systems inspired by SCD. Initially, both LCD and SCD are performed by humans. The study suggests humans require (a) a larger duration around the change point and (b) language-specific prior exposure, for performing LCD as compared to SCD. The larger duration requirement is incorporated by increasing the analysis window length of the unsupervised distance-based approach. This leads to a relative performance improvement of (29.1%) and (2.4%), and a priori language knowledge provides a relative improvement of (31.63%) and (4.01%) on the synthetic and practical codeswitched datasets, respectively. The performance difference between the practical and synthetic datasets is mostly due to differences in the distribution of the monolingual segment duration.

Model order reduction technique provides an effective way to reduce computational complexity in large-scale circuit simulations. This paper proposes a new model order reduction method for delay circuit systems based on Hermite expansion technique. The presented method consists of three steps i.e., first the delay elements are approximated using the recursive relation of Hermite polynomials, then in the second step, the reduced order is estimated for the delay circuit system using a delay truncation in the Hermite domain and in the third step, a multi-order Arnoldi process is computed for obtaining the projection matrix. In the following, the reduced order delay circuit model is obtained by the projection matrix. Moment matching and passivity properties of the reduced circuit system are also analyzed. Two circuit examples with delay components are performed to verify the effectiveness of the proposed MOR approach.