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- Khan, Muhammad Gufran, et al.
(författare)
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Non-coherent detection of impulse radio UWB signals based on fourth order statistics
- 2011
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Ingår i: Wireless Personal Communications. - Springer. - 0929-6212.
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Tidskriftsartikel (refereegranskat)abstract
- Low-complex and low power non-coherent energy detector (ED) is interesting for low data rate impulse radio (IR) ultra wideband (UWB) systems but, compared to coherent receivers, it suffers from a loss in performance due to low signal-to-noise ratio (SNR) at the detector. In addition, the performance of an ED strongly depends on the integration interval (window size) of the integrator and the window position. A non-coherent kurtosis detector (KD) and a fourth-order detector (FD), which can discriminate between Gaussian noise signals and non-Gaussian IR-UWB signals by directly estimating the fourth-order moment of the received signal, are presented. The performance of the detectors is evaluated using real channels measured in a corridor, an office and a laboratory environment. The results show that bit-error-rate (BER) performance of the proposed KD receiver is better than the ED receiver only under certain conditions, while the FD receiver is slightly better than the ED in low SNR region and its performance improves as the SNR increases. In addition, the performance of the FD receiver is less sensitive to overestimation of the integration interval making it relatively robust to variations of the channel delay spread. Finally, a criteria for the selection of integration time of the proposed detector is suggested.
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| 2. |
- Khan, Muhammad Gufran, et al.
(författare)
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Non-Coherent Fourth-Order Detector for Impulse Radio Ultra Wideband Systems: Empirical Evaluation Using Channel Measurements
- 2013
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Ingår i: Wireless Personal Communications. - Springer. - 0929-6212. ; 68:1, s. 27-46
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Tidskriftsartikel (refereegranskat)abstract
- Low-complex and low-power non-coherent energy detectors (EDs) are interesting for low data rate impulse radio (IR) ultra wideband (UWB) systems, but suffer from a loss in performance compared to coherent receivers. The performance of an ED also strongly depends on the integration interval (window size) of the integrator and the window position. This paper presents a non-coherent fourth-order detector (FD) which can discriminate between Gaussian noise signals and non-Gaussian IR-UWB signals by directly estimating the fourth-order moment of the received signal. The performance of the detectors is evaluated using realistic channels measured in a corridor, an office and a laboratory environment. The results show that bit-error-rate (BER) performance of the proposed FD receiver is slightly better than the ED in low signal-to-noise ratio (SNR) region and its performance improves as the SNR increases. In addition, BER of the FD receiver is less sensitive to overestimation of the integration interval making it relatively robust to variations of the channel delay spread. Finally, a criteria for the selection of integration time of the proposed detector is suggested.
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| 5. |
- Ström Bartunek, Josef, et al.
(författare)
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Adaptive Fingerprint Image Enhancement with Emphasis on Preprocessing of Data
- 2013
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Ingår i: IEEE Transactions on Image Processing. - IEEE. - 1941-0042 (online) .- 1057-7149 (print). ; 22:2, s. 644-656
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Tidskriftsartikel (refereegranskat)abstract
- This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are; preprocessing, global analysis, local analysis and matched filtering. In the pre-processing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated towards the NIST developed NBIS software for fingerprint recognition on FVC databases.
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