Temat: wiener filtering - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Frequency Offset Compensation for OFDM Systems Using a Combined Autocorrelation and Wiener Filtering Scheme
Autorzy:: Ramadan Ali, A.
Khanzada, T. J.
Omar, A.
Powiązania:: https://bibliotekanauki.pl/articles/308065.pdf
Data publikacji:: 2010
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: channel characterization
frequency offset
OFDM measurement
Wiener filtering
Opis:: One of the orthogonal frequency division multiplexing (OFDM) system disadvantages is its sensitivity to frequency offset and phase noise, which lead to losing the orthogonality between the subcarriers and thereby degrade the system performance. In this paper a joint scheme for frequency offset and pilot-based channel estimation is introduced in which the frequency offset is first estimated using an autocorrelation method, and then is fined further by applying an iterative phase correction by means of pilot-based Wiener filtering method. In order to verify the capability of the estimation algorithm, the scheme has been implemented and tested using a real measurement system in a multipath indoor environment. The results show the algorithm capability of compensating for the frequency offset with different transmission and channel conditions.
Źródło:: Journal of Telecommunications and Information Technology; 2010, 1; 40-47
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Wiener Filtering Applied to Conducted EMI Estimation in Soft Switching Inverter
Autorzy:: Musznicki, P.
Chrzan, P. J.
Mandrek, S.
Powiązania:: https://bibliotekanauki.pl/articles/1203943.pdf
Data publikacji:: 2008
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie
Tematy:: wiener filtering
estimation
electromagnetic
interference
resonant power
conversion
Opis:: This paper presents an estimation method of the conducted electromagnetic interference EMI emissions in soft switching inverters. Estimation process is carried out by a number of Wiener filters, which represent different operation conditions as reflected through subsequent power converter states determined by initial commutation event conditions and propagation paths layout. Filters are fed by a semiconductor power switch voltage or current waveforms regarded as sources of perturbation. The EMI emissions are measured on the line impedance stabilization network LISN terminals. Optimal filter adaptation is effected in the frequency domain by measuring input and cross power signal spectra. Analysis of parallel quasi resonant dc link voltage inverter PQRDCLI is outlined to distinguish filters assigned for inverter operation and those for an external DC/DC converter interaction. Experimental results are given to illustrate the Wiener filtering estimation quality. Possibility of detailed decomposition of the LISN-EMI waveforms is depicted in both time and frequency domain. Comparative analysis of frequency responses for PQRDCLI link voltage changes is given.
Źródło:: Electrical Power Quality and Utilisation. Journal; 2008, 14, 2; 25-28
1896-4672
Pojawia się w:: Electrical Power Quality and Utilisation. Journal
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: A Comparative Study of Various Edge Detection Techniques for Underwater Images
Autorzy:: Awalludin, Ezmahamrul Afreen
Arsad, Tengku Noorfarahana T.
Yussof, Wan Nural Jawahir Hj Wan
Bachok, Zainudin
Hitam, Muhammad Suzuri
Powiązania:: https://bibliotekanauki.pl/articles/2058499.pdf
Data publikacji:: 2022
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: edge detection
mean square error
median filtering
peak signal to noise
wiener filtering
Opis:: Nowadays, underwater image identification is a challenging task for many researchers focusing on various ap plications, such as tracking fish species, monitoring coral reef species, and counting marine species. Because underwater im ages frequently suffer from distortion and light attenuation, pre-processing steps are required in order to enhance their quality. In this paper, we used multiple edge detection techniques to determine the edges of the underwater images. The pictures were pre-processed with the use of specific techniques, such as enhancement processing, Wiener filtering, median filtering and thresholding. Coral reef pictures were used as a dataset of underwater images to test the efficiency of each edge detection method used in the experiment. All coral reef image datasets were captured using an underwater GoPro camera. The performance of each edge detection technique was evaluated using mean square error (MSE) and peak signal to noise ratio (PSNR). The lowest MSE value and the highest PSNR value represent the best quality of underwater images. The results of the experiment showed that the Canny edge detection technique outperformed other approaches used in the course of the project.
Źródło:: Journal of Telecommunications and Information Technology; 2022, 1; 23--33
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Deep Neural Network for Supervised Single-Channel Speech Enhancement
Autorzy:: Saleem, Nasir
Irfan Khattak, Muhammad
Ali, Muhammad Yousaf
Shafi, Muhammad
Powiązania:: https://bibliotekanauki.pl/articles/177497.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:: deep neural network
intelligibility
speech enhancement
speech quality
supervised learning
Wiener filtering
Opis:: Speech enhancement is fundamental for various real time speech applications and it is a challenging task in the case of a single channel because practically only one data channel is available. We have proposed a supervised single channel speech enhancement algorithm in this paper based on a deep neural network (DNN) and less aggressive Wiener filtering as additional DNN layer. During the training stage the network learns and predicts the magnitude spectrums of the clean and noise signals from input noisy speech acoustic features. Relative spectral transform-perceptual linear prediction (RASTA-PLP) is used in the proposed method to extract the acoustic features at the frame level. Autoregressive moving average (ARMA) filter is applied to smooth the temporal curves of extracted features. The trained network predicts the coefficients to construct a ratio mask based on mean square error (MSE) objective cost function. The less aggressive Wiener filter is placed as an additional layer on the top of a DNN to produce an enhanced magnitude spectrum. Finally, the noisy speech phase is used to reconstruct the enhanced speech. The experimental results demonstrate that the proposed DNN framework with less aggressive Wiener filtering outperforms the competing speech enhancement methods in terms of the speech quality and intelligibility.
Źródło:: Archives of Acoustics; 2019, 44, 1; 3-12
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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