Randomised pulse width modulation (RPWM) technique has become a viable alternative to deterministic pulse width modulation (DPWM). By spreading the power spectrum in a continuous noise, this new technique better complies with electromagnetic compatibility (EMC) requirements for conducted electromagnetic interferences (EMI) and allows reducing the emitted acoustic noise in variable speed drives (VSDs). The most popular RPWM schemes are randomised pulse position modulation (RPPM) and randomised carrier frequency modulation (RCFM). The combination (RCFM-RPPM) or dual RPWM (DRPWM) has also been proposed. In this article, we propose an optimised DRPWM (ODRPWM) for the three-phase inverter. First, the modulating principle is proposed, and then, a mathematical model of power spectral density (PSD) of the output voltage is developed and validated for the three schemes, namely RPPM, RCFM and RCFM-RPPM. PSD analysis shows that the proposed scheme is more effective on spreading PSD. Moreover, this analysis reveals optimal parameters of randomisation for a maximum spread of the PSD. The optimisation problem is then modelled and solved using two powerful non-linear methods. 相似文献
In this paper, we propose a hybrid classifier fusion scheme for motor unit potential classification during electromyographic (EMG) signal decomposition. The scheme uses an aggregator module consisting of two stages of classifier fusion: the first at the abstract level using class labels and the second at the measurement level using confidence values. Performance of the developed system was evaluated using one set of real signals and two sets of simulated signals and was compared with the performance of the constituent base classifiers and the performance of a one-stage classifier fusion approach. Across the EMG signal data sets used and relative to the performance of base classifiers, the hybrid approach had better average classification performance overall. For the set of simulated signals of varying intensity, the hybrid classifier fusion system had on average an improved correct classification rate (CCr) (6.1%) and reduced error rate (Er) (0.4%). For the set of simulated signals of varying amounts of shape and/or firing pattern variability, the hybrid classifier fusion system had on average an improved CCr (6.2%) and reduced Er (0.9%). For real signals, the hybrid classifier fusion system had on average an improved CCr (7.5%) and reduced Er (1.7%). 相似文献
Most image processing applications require noise elimination. For example, in applications where derivative operators are applied, any noise in the image can result in serious errors. Impulsive noise appears as a sprinkle of dark and bright spots. Transmission errors, corrupted pixel elements in the camera sensors, or faulty memory locations can cause impulsive noise. Linear filters fail to suppress impulsive noise. Thus, non-linear filters have been proposed. Windyga's peak-and-valley filter, introduced to remove impulsive noise, identifies noisy pixels and then replaces their values with the minimum or maximum value of their neighbors depending on the noise (dark or bright). Its main disadvantage is that it removes fine image details. In this work, a variation of the peak-and-valley filter is proposed to overcome this problem. It is based on a recursive minimum–maximum method, which replaces the noisy pixel with a value based on neighborhood information. This method preserves constant and edge areas even under high impulsive noise probability. Finally, a comparison study of the peak-and-valley filter, the median filter, and the proposed filter is carried-out using different types of images. The proposed filter outperforms other filters in the noise reduction and the image details preservation. However, it operates slightly slower than the peak-and-valley filter. 相似文献
Massive capacity demand is a major impetus behind the advances, in various ways, of today and near future wireless communication networks. To face this challenge, more wireless spectrum is needed, efficient usage of this spectrum is necessary, and adequate architectures are required. In this paper, we present a conceptual solution based on a cognitive-radio-inspired cellular network, for integrating idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. We describe the conceptual architecture of this integrating network, referred to as Integrating cognitive-radio-inspired cellular network (I-CRICNet), and present a cooperative spectrum-harvesting scheme that keeps the former supplied with spectrum resources. In the latter scheme, we make extensive use of cross-correlated sequences (CSSs), for events signaling purposes. This choice is motived by the particularly interesting characteristics of the CSSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.
Analysis and experiment of a new leaky nrd guide based on a grating structure is described. Analysis employs a mode coupling procedure which yields highly accurate results while presenting the advantage of simplicity and ease of manipulation. Numerical values for the phase and leakage constants are presented and the role of each grating parameter is assessed. Theoretical results are compared with experimental data for different geometric and constitutive parameters and reasonable agreement between them is obtained. 相似文献