DSpace :: Home

Welcome to the BUT Digital Library - an institutional repository operated by the Central Library on the DSpace system.

Do you want to deposit your article or preceedings into Digital Library? It is very simple. You can find all the information in the manual published online on BUT Portal of libraries.

Central Library supports open access to scientific publishing - Open Access.

You can also request for grant for open publishing from Open Access Fund You can find more information OA fund web page.

Into the Digital Library is integrated citation manager Citace PRO. It will allow you to easily create a bibliographic citation or save a record in the manager.

Communities in DSpace

Select a community to browse its collections.

Now showing 1 - 10 of 10

Recent Submissions

Access status: Open Access ,
A Two-Stage Optimization Framework for Radar Jamming Effectiveness Evaluation
(Společnost pro radioelektronické inženýrství, 2025-12) Wang, J.; Liu, Y.; Li, C.; Wang, Z.; Li, Y.
In complex electromagnetic environments, radar signals intercepted by jammers often contain biased data due to factors such as radar mode switching, electromagnetic interference, and receiver noise. To address this challenge, this paper proposes a two-stage optimization framework for jamming effect evaluation from the jammerâ s perspective. In the first stage, a pre-evaluation is conducted using an entropy-optimized K-means discretization algorithm (KDEOA) to adaptively partition pulse descriptor word (PDW) parameters, enhancing robustness against noise. A GCSAO-LSSVM model is then employed to improve classification accuracy through optimal parameter tuning and a periodic oscillation mutation strategy. In the second stage, an improved entropy weight method (IEWM) integrating Tsallis entropy, kernel density standardization, and game theory is used for objective weighting, followed by an enhanced TOPSIS method (ITOPSIS) incorporating interquartile range standardiza-tion and dynamic ideal solution fusion for quantitative scoring. Experimental results demonstrate that the pro-posed framework achieves the highest pre-evaluation accuracy across all noise levels (up to 50% contamination), with IEWM exhibiting the lowest weight variation rate (0.11â 0.23%) and ITOPSIS showing the strongest correlation (0.7290) with baseline scores under high noise. The main limitations include sensitivity to severe signal distortion and assumption of stable radar behavior. This approach enables accurate, non-cooperative jamming assessment and supports robust decision-making in cognitive electronic warfare.
Access status: Open Access ,
High-Precision Indoor Localization via Dual-Modal AOA/TOA Fusion with Deep Learning and Particle Filters
(Společnost pro radioelektronické inženýrství, 2025-12) Yao, X.; Xu, Z.; Qiang, F.
As the era of IoT and artificial intelligence advances, the demand for high-precision indoor positioning systems continues to grow. Achieving accurate positioning in indoor environments remains challenging due to the presence of obstacles and signal interference, especially in Non-Line-of-Sight (NLOS) conditions. To address these challenges, this paper proposes a novel indoor positioning algorithm based on the fusion of Angle of Arrival (AOA) and Time of Arrival (TOA) data. A hybrid model combining Asymptotic Gradient Boosted Regression Trees (GBRT) and Elastic Net (EN) is used to reduce AOA measurement errors in NLOS environments, followed by the application of the Levenberg-Marquardt (LM) optimization algorithm to enhance localization accuracy. Experimental results show a significant reduction in positioning error, with an average error of 0.47 meters, representing a 41.25% improvement compared to the KF+WLS algorithm. Meanwhile, to improve TOA positioning, a deep learning-based TOA fingerprinting algorithm is proposed, this algorithm captures complex spatiotemporal features in TOA data, leading to a 25.00% and 15.22% reduction in root mean square error (RMSE) compared to the WKNN and WLS algorithms, respectively. Finally, a fusion strategy based on Particle Filtering (PF) is introduced to combine AOA and TOA data, achieving further RMSE reductions of 35.42% and 20.51%, compared to individual AOA and TOA methods.
Access status: Open Access ,
A Broadband Low-Profile Dual-Polarized Antenna Based on a Metasurface
(Společnost pro radioelektronické inženýrství, 2025-12) Dai, X.; Zhao, J.; Shen, Z.; Hong, H.; Li, G.
This article presents a wideband low-profile dual-polarization antenna based on a metasurface (MS). The antenna consists of a 4Ã 4 metasurface array made up of 16 circular metal patches, a radiating patch, and a metallic ground plane. The metasurface excites the surface waves of the radiating patch to generate multiple resonant points, thereby broadening the antenna bandwidth. In addition, two rectangular cross-slot structures at the center of the patch enhance port isolation. Finally, a prototype with dimensions of 46 mm Ã 46 mm Ã 3.2 mm (1.28Î»â Ã 1.28Î»â Ã 0.88Î»â ) was fabricated. Measurement results show that the antenna achieves a return loss better than -10 dB and an isolation better than -16 dB within the operating bandwidth of 6.38â 10.3 GHz. It can be concluded that the experimental results of the antenna are in good agreement with the simulation results.
Access status: Open Access ,
Hybrid Small-Signal Modeling of GaN HEMT Enhanced by the Integration of SVD and RIME Optimization
(Společnost pro radioelektronické inženýrství, 2025-12) Zhang, J.; Wang, K.; Wang, J.; Wei, H.; Chang, J.; Yao, J.; Zhang, L.
For the 20-element small-signal model of GaN HEMT, a combination of the singular value decomposition (SVD) algorithm and the frost ice optimization algorithm is proposed in this paper to extract and optimize the intrinsic parameters of the small-signal model. When the traditional algorithm is employed for parameter extraction, issues of low extraction accuracy and efficiency are encountered. By introducing an optimization algorithm for parameter extraction, the accuracy and efficiency of the process are enhanced. However, previous studies have focused on improving the optimization algorithm to optimize the eigenparameters of GaN HEMT without taking into account the correlation among the parameters within the model. In this study, the SVD algorithm is utilized to process the real and imaginary parts of the intrinsic model Y-parameters, thereby strengthening the correlation between the intrinsic parameters. Subsequently, the new intrinsic model Y-parameters and the RIME algorithm are employed to extract the intrinsic parameters. The experimental results demonstrate that the combination of the SVD algorithm and the frost ice optimization algorithm breaks the isolation between the eigenparameters, improves the parameter correlation, and can accurately extract and optimize the eigenparameters of the small-signal model within the frequency range of 0.5 - 20.5 GHz.
Access status: Open Access ,
Fusion Based Method for Wide Band Speech Reconstruction Over Legacy Telephone Networks
(Společnost pro radioelektronické inženýrství, 2025-12) Emani, R. P. K.; Telagathoti, P.; Nizampatanam, P.
Public Switched Telephone Networks (PSTNs) are limited to Restricted Band (RB) speech in the 0-4 kHz range, which reduces speech quality compared to Wideband (WB) speech (0-8 kHz). This study proposes a transform-based hybrid steganography technique combining Curvelet Transform (CT) and Fast Fourier Transform (FFT) to enhance RB speech quality while maintaining full PSTNs compatibility. The Curvelet Transform, capable of representing directional and edge-like features across multiple scales and angles, allows efficient capture of speech components such as formant transitions and unvoiced consonants, which are critical for improving quality and intelligibility. In the proposed approach, WB speech is decomposed into RB and Extended Band (4-8 kHz) components. Detailed coefficients of the RB are extracted using CT, and spread parameters of the Extended Band are embedded within the RB signal. Inverse CT and FFT are performed to form a Composite Restricted Band (CRB) signal for transmission. At the receiver, the embedded parameters are recovered to reconstruct the Extended Band, which is merged with the CRB signal to yield a high-quality Reconstructed Wideband (RWB) signal. Tests with participants aged 60-75 years demonstrated superior performance over conventional methods, with strong robustness to channel and quantization noise.