• Journal of Information Processing Systems
• /
• 제15권5호
• /
• pp.1243-1257
• /
• 2019

As current algorithms unable to perform effective fusion processing of unknown complex radar signals lacking database, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complex radar signals based on evidence theory as a solution to this problem. Specifically, the real-time database is initially established, accompanied by similarity model based on parameter type, and then similarity matrix is calculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity of parameters concerning each signal and the trust value concerning target framework of each signal in order. The signals are ultimately combined and perfected. The results of simulation experiment reveal that the proposed algorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency and less time, maintaining stable processing even of considerable samples.

• 한국통신학회논문지
• /
• 제30권9C호
• /
• pp.913-921
• /
• 2005

일반적인 bandpass sampling 방법인 real bandpass sampling 기법은 하향변환(downconversion)을 시행할 때 음의 주파수 대역의 RF 신호와의 에일리어싱(aliasing) 현상을 피해야 하므로 신중한 sampling 주파수 선택이 요구된다. 더욱이 다중신호(multiple signals)가 하향변환 될 경우에 이 sampling 방법은 더욱 많은 제약이 따르게 된다. 그러나 Hilbert 변환을 사용하는 complex bandpass sampling 방법은 음의 주파수 영역의 신호를 제거함으로써, real bandpass sampling 기법보다 유연하고 넓은 sampling 주파수 범위를 제공하며, 또한 더욱 낮은 sampling 주파수를 얻을 수 있는 장점이 있다. 본 논문에서는 이러한 complex bandpass sampling의 특징을 사용하여, 다중 신호를 하나의 통신 기기에서 동시에 하향 변환하는 수신기의 구조를 제시한다. 그리고 하나 또는 2개 신호의 하향변환에 관한 내용으로 제한하지 않고 N개의 신호로 확장하여 유효 sampling 주파수 영역 및 보호대역(guard-band)이 고려된 sampling 가능 최소 주파수에 관한 수식들을 일반화한다. 또한 모의실험을 통해 유도된 수식들을 증명한다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제55권7호
• /
• pp.332-334
• /
• 2006

In this paper, we present an equalization scheme for 8-VSB signals for the ATSC DTV system. We propose a complex feedback filter and complex feedback sample generator for DFE to equalize 8-VSB signals in order to efficiently remove multipath distortions causing leakages from the qudrature component. We show that the proposed structure outperforms the conventional DFE used for the digital VSB which uses a real-valued feedback filter with real-valued decisions.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2001년도 하계종합학술대회 논문집(5)
• /
• pp.89-92
• /
• 2001

For the diagnosis of arrhythmia in the heart system, the QRS complex of ECG signals is used in many cases. The rejection of the noise in ECG signals is important to acquisition of exact QRS complex. This paper presents some experimental results about instantaneous bandwidth estimation and noise rejection of ECG signals with the purpose of rejection of the 60 Hz power noise and the motion artifacts such as EMG signals and contact noise. ECG signals corrupted by noise are cleaned by using the variable bandwidth filter. For the filtering of ECG signals with noise, the instantaneous bandwidth of the signals is estimated by analysis of time-frequency representation of ECG signal.

• 전자공학회논문지S
• /
• 제35S권5호
• /
• pp.48-58
• /
• 1998

In this paper, we proposed a new algorithm using characteristics of th ereconstructed phase trajectory by topological mapping developed for a real-tiem detection of the QRS complexes of ECG signals. Using fill-factor algorithm and mutual information algorithm which are in genral used to find out the chaotic characteristics of sampled signals, we inferred the proper mapping parameter, time delay, in ECG signals and investigated QRS detection rates with varying time delay in QRS complex detection. And we compared experimental time dealy with the theoretical one. As a result, it shows that the experimental time dealy which is proper in topological mapping from ECG signals is 20ms and theoretical time delays of fill-factor algorithm and mutual information algorithm are 20.+-.0.76ms and 28.+-.3.51ms, respectively. From these results, we could easily infer that the fill-factor algorithm in topological mapping from one-dimensional sampled ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper time delay. Also with the proposed algorithm which is very simple and robust to low-frequency noise as like baseline wandering, we could detect QRS complex in real-time by simplifying preprocessing stages. For the evaluation, we implemented the proposed algorithm in C-language and applied the MIT/BIH arrhythmia database of 48 patients. The proposed algorithm provides a good performance, a 99.58% detection rate.

• Journal of Electrical Engineering and Technology
• /
• 제6권2호
• /
• pp.154-160
• /
• 2011

A new algorithm for estimating the fundamental frequency of power system signals is presented. The proposed algorithm consists of two stages: orthogonal decomposition and a complex Prony analysis. First, the input signal is decomposed into two orthogonal components using cosine and sine filters, and a variable window is adapted to enhance the performance of eliminating harmonics. Then a complex Prony analysis that is proposed in this paper is used to estimate the fundamental frequency by approximating the cosine-filtered and sine-filtered signals simultaneously. To evaluate the performance of the algorithm, amplitude modulation and harmonic tests were performed using simulated test signals. The performance of the algorithm was also assessed for dynamic conditions on a single-machine power system. The Electromagnetic Transients Program was used to generate voltage signals for a load increase and single phase-to-ground faults. The performance evaluation showed that the proposed algorithm accurately estimated the fundamental frequency of power system signals in the presence of amplitude modulation and harmonics.

• 대한의용생체공학회:의공학회지
• /
• 제43권4호
• /
• pp.280-289
• /
• 2022

In this paper, we present a QRS-complex detection algorithm to calculate an accurate heartbeat and clearly recognize irregular rhythm from ECG signals. The conventional Pan-Tompkins algorithm brings false QRS detection in the derivative when QRS and noise signals have similar instant variation. The proposed algorithm uses amplitude differences in 7 adjacent samples to detect QRS-complex which has the highest amplitude variation. The calculated amplitude is cubed to dominate QRS-complex and the moving average method is applied to diminish the noise signal's amplitude. Finally, a decision rule with a threshold value is applied to detect accurate QRS-complex. The calculated signals with Pan-Tompkins and proposed algorithms were compared by signal-to-noise ratio to evaluate the noise reduction degree. QRS-complex detection performance was confirmed by sensitivity and the positive predictive value(PPV). Normal ECG, muscle noise ECG, PVC, and atrial fibrillation signals were achieved which were measured from an ECG simulator. The signal-to-noise ratio difference between Pan-Tompkins and the proposed algorithm were 8.1, 8.5, 9.6, and 4.7, respectively. All ratio of the proposed algorithm is higher than the Pan-Tompkins values. It indicates that the proposed algorithm is more robust to noise than the Pan-Tompkins algorithm. The Pan-Tompkins algorithm and the proposed algorithm showed similar sensitivity and PPV at most waveforms. However, with a noisy atrial fibrillation signal, the PPV for QRS-complex has different values, 42% for the Pan-Tompkins algorithm and 100% for the proposed algorithm. It means that the proposed algorithm has superiority for QRS-complex detection in a noisy environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권10호
• /
• pp.4814-4834
• /
• 2018

This paper presents an architecture for wireless sensor networks (WSNs) with blind source separation (BSS) applied to retrieve the received mixing signals of the sink nodes first. The little-to-no need of prior knowledge about the source signals of the sink nodes in the BSS method is obviously advantageous for WSNs. The optimization problem of the BSS of multiple independent source signals with complex and noncircular distributions from observed sensor nodes is considered and addressed. This paper applies Castella's reference-based scheme to Novey's negentropy-based algorithms, and then proposes a novel fast fixed-point (FastICA) algorithm, defined as the reference-signal negentropy complex FastICA (RSNT-cFastICA) for complex-valued noncircular-distribution source signals. The proposed method for the sink nodes is substantially more efficient than Novey's quasi-Newton algorithm in terms of computational speed under large numbers of samples, can effectively improve the power consumption effeciency of the sink nodes, and is significantly beneficial for WSNs and wireless communication networks (WCNs). The effectiveness and performance of the proposed method are validated and compared with three related BSS algorithms through theoretical analysis and simulations.

• Smart Structures and Systems
• /
• 제7권1호
• /
• pp.59-82
• /
• 2011

In this study, an output-only modal identification approach is proposed for decentralized wireless sensor nodes used for linear structural systems. The following approaches are implemented to achieve the objective. Firstly, an output-only modal identification method is selected for decentralized wireless sensor networks. Secondly, the effect of time-unsynchronization is assessed with respect to the accuracy of modal identification analysis. Time-unsynchronized signals are analytically examined to quantify uncertainties and their corresponding errors in modal identification results. Thirdly, a modified approach using complex mode shapes is proposed to reduce the unsynchronization-induced errors in modal identification. In the new way, complex mode shapes are extracted from unsynchronized signals to deal both with modal amplitudes and with phase angles. Finally, the feasibility of the proposed approach is evaluated from numerical and experimental tests by comparing with the performance of existing approach using real mode shapes.

• ETRI Journal
• /
• 제43권6호
• /
• pp.991-1003
• /
• 2021

Automatic modulation classification is essential in radar emitter identification. We propose a cascade classifier by combining a support vector machine (SVM) and convolutional neural network (CNN), considering that noise might be taken as radar signals. First, the SVM distinguishes noise signals by the main ridge slice feature of signals. Second, the complex envelope features of the predicted radar signals are extracted and placed into a designed CNN, where a modulation classification task is performed. Simulation results show that the SVM-CNN can effectively distinguish radar signals from noise. The overall probability of successful recognition (PSR) of modulation is 98.52% at 20 dB and 82.27% at -2 dB with low computation costs. Furthermore, we found that the accuracy of intermediate frequency estimation significantly affects the PSR. This study shows the possibility of training a classifier using complex envelope features. What the proposed CNN has learned can be interpreted as an equivalent matched filter consisting of a series of small filters that can provide different responses determined by envelope features.