IET Signal Processing刊发的主题包括单维与多维、线性与非线性、递归与非递归数字滤波器和多速率滤波器组的算法进展,以及混沌理论和神经网络在信号处理中的应用。 IET Systems Biology Impact Factor: 1.000 5-year Impact Factor 1.123 CiteScore: 2.3 主编: Kwang-Hyun Cho(韩国科学技术院) IET Systems Biology涵...
Topics include, but are not limited to: Applications of signal processing, equalisation, coding, error detection and error correction; Videotelephony, videoconferencing and multimedia communications; Communications layers, Internet Protocols, Internet telephony and VoIP; Fading channel, mobile systems, ...
Signal Processing Software Publisher John Wiley & Sons Inc. H-Index 41 Publication type Journals ISSN 20474938, 20474946 Coverage 2012-2023 Information Homepage How to publish in this journal iet_bmt@theiet.org Scope The scope of the journal is intentionally relatively wide. While focusing on core...
The expansion factor is set to grow exponentially to ensure a large enough time context window, which efficiently utilises the long-term dependence of the signal. convolution is employed to model the correlation between channels as well as achieve channel adaptation. After normalisation, the output...
摘要:The direction of arrival (DOA) and amplitude-phase (AP) of source signal can be estimated through array signal processing, while the process of information acquisition has not been described by information theory yet. In this study, the authors propose a novel spatial information theory frame...
The influence of noise presents a significant problem in PMU signal processing. Various filtering methods can be used to reduce the influence of noise. For example, Kalman filtering [37] is a representative approach to relieve the noise in state estimation. The least squares method [38] and the...
In fact, by choosing a pool of randomisation sequences with certain statistical properties, they could also be used to condition the signal to meet physical layer transmission requirements such as bandwidth, envelope and so on. They quantify the potential of the proposed method by demonstrating it...
the transmitted signal of every element has an impact on each other via sidelobes. The sidelobes could cancel each other for most ranges. The interaction between sidelobes can eventually give rise to the low SLL. However, the peak sidelobe is slightly increased in Fig.7 bcompared with that ...
Hybrid models have outperformed signal models such as the LSTM in recent years owing to the nonstationary nature of load data. The model's accuracy is increased with the use of LSTM-based SAM. This strategy is useful for assigning weights to certain pieces of information. This method can be...
Since human body movement and different postures cause attenuation and data disruption in the received signal power, we can add another factorcalled path loss in Equation (3). Path loss is an attenuation factor between transmitted and received power which is measured in decibels (dB). It is a...