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- ItemReconstruction of Mixed Boundary Objects and Classification Using Deep Learning and Linear Sampling Method(Společnost pro radioelektronické inženýrství, 2024-06) Harisha, S. B.; Mallikarjun, E.; Amit, M.The linear sampling method is a simple and reliable linear inversion technique for determining the morphological features of unknown objects under investigation. Nevertheless, there are many challenges that this method depends on the frequency of operation and it is unable to produce satisfactory results for objects with complex shapes. This paper proposes a hybrid model, which combines conventional linear sampling method and deep learning for the reconstruction of mixed boundary objects. In this approach, the initial approximation of mixed boundary objects derived from linear sampling method serves as the training data for the U-Net based convolutional neural network. The network then learns to correlate this approximation with the corresponding ground truth profiles. Along with the reconstruction of mixed boundary objects, they are also classified as dielectric or conductor, and count of each object type are measured. Furthermore, the low-frequency and high-frequency characteristics of the linear sampling method are analyzed, and its limitations are overcome by combining it with a deep learning approach. The effectiveness of the proposed model is validated using several examples of synthetic and experimental data. The results demonstrate that the proposed method outperforms the conventional Linear sampling method in terms of accuracy.
- ItemIdentification of the Linear Systems of the Wiener Hammerstein RF Power Amplifier Model Using DFT Analysis(Společnost pro radioelektronické inženýrství, 2024-06) Yesil, S.; Yilmaz, A. O.This paper presents a novel method for identification of the sub-system parameters of a Wiener-Hammerstein Nonlinear (WHNL) system that is used for modeling RF Power Amplifier characteristics. The proposed method first isolates the overall linear system from the memoryless nonlinearity by exploiting the Bussgang decomposition method. Then, Discrete Fourier Transform (DFT) analysis is used for the estimation of the inner linear system. Finally, the outer linear system parameters are updated based on the inner system estimation. The estimated systems are then used to model the target system for an In-Band-Full-Duplex (IBFD) scenario. Performance of Self-Interferene Cancellation (SIC) has been evaluated under the existence of Signal-of-Interest (SoI). Error Vector Magnitude (EVM) metric of the SoI is used to compare with a Half-Duplex (HD) receiver under various inner linear system parameters. SIC performance has been examined with respect to the changing power levels of the SoI and self-interference signal for various delay and gain values of a practical two-tap inner linear system. The benefit of modeling the inner linear system has been revealed by comparing the SIC performance with Hammerstein nonlinear model. The performance has also been compared to well known black box models such as Generalized Memory Polynomial (GMP) and Artificial Neural Networks (ANN).
- ItemA Novel IoT Intrusion Detection Model Using 2dCNN-BiLSTM(Společnost pro radioelektronické inženýrství, 2024-06) Xiang, R. H.; Li, S. S.; Pan, J. L.With the continuous advancement of Internet of Things (IoT) intelligence, IoT security issues have become more and more prominent in recent years. The research on IoT security has become a hot spot. A lightweight IoT intrusion detection model fusing a convolutional neural network, bidirectional long short-term memory network is proposed. It aims to improve processed data security and attack detection accuracy. First, sampling is performed by a hybrid sampling algorithm fusing SMOTE and ENN. Its aim is to minimize the impact of imbalanced-data and ensure data quantity in the process. Then, the data features are extracted by 2-dimensional convolutional neural network (2dCNN), and the effect of useless information is reduced by mean pooling and maximum pooling, so it can be adapted to the demanding resource environment of the IoT. On this basis, long-range dependent temporal features are extracted using bidirectional long short-term memory (BiLSTM), which aims to fully extract data features to improve detection accuracy in the limited resource environment. Finally, the algorithm is validated on the UNSW_NB15 dataset, and the results of the experiments reaches 93.5% at Accuracy, 86.4% at Precision, 85.3% at Recall and 85.8% at F1-Score. According to the results, the proposed algorithm can generate higher-quality samples, achieve higher detection rate with faster inference time and spend lower memory costs.
- ItemBalanced Linear-Phase Bandpass Filter Equalized with Negative Group Delay Circuit(Společnost pro radioelektronické inženýrství, 2024-06) Wang, Z. C.; Wang, Z. B.; Gao, M.; Liu, H.; Fang, S.A novel balanced linear-phase bandpass filter is proposed to achieve differential-mode linear-phase filtering and common-mode suppression characteristics. The balanced linear-phase bandpass filter consists of a proposed compact balanced bandpass filter and negative group delay circuits, in which the circuits are loaded on the ports of the filter as branches. The linear-phase performance is achieved through negative compensation of group delay fluctuations using negative group delay circuit equalization. In order to verify the design method, a 3-order balanced linear-phase bandpass filter is designed, simulated, manufactured, and measured. The results show that the group delay fluctuation of the balanced bandpass filter has been reduced by 89.6 % from 1.110 to 0.115 ns. The minimum common-mode suppression within the passband is 41.4 dB. The proposed balanced bandpass filter has an excellent differential-mode linear-phase transmission and common-mode suppression performances.
- ItemA Quadruple Band-Notched SWB MIMO Antenna with Enhanced Isolation Using Wiggly Line(Společnost pro radioelektronické inženýrství, 2024-06) Chaudhary, A. K.; Manohar, M.A novel quadruple band-notched spatial diversity/MIMO antenna for super wideband (SWB) application is investigated. The proposed antenna comprises two identical tapered semicircular radiators with two microstrip feedlines and a common slotted ground plane (CSGP), contributing a wide impedance bandwidth from 1.88-30 GHz. Further, a wiggly-line-decoupling-structure (WLDS) is introduced among the radiating ports to maximize the average isolation, more than 24 dB. The first band-notched functionality at 2.4 GHz is produced by etching a meandering slot on the CSGP, while the remaining three notch bands at 3.5, 5.5, and 7.5 GHz are obtained by implanting open-ended-semicircular (OES), complementary-split-ring-resonator (CSRR), and elliptical-split-ring-resonator (ESRR) slots in each radiating patch. The designed and fabricated results for the two and four elements are analyzed, which exhibit wideband characteristics, stable radiation pattern, higher efficiency (above 85%), and reasonably high peak gain within the working frequency, excluding the quadruple notched bands. Moreover, other essential parameters such as ECC, DG, CCL, and TARC have also been analyzed, showing the antenna's usefulness for radar imaging, cognitive radio, military, and long-range RF applications.
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