scholarly journals Wavelet based methods for improved wind profiler signal processing

2001 ◽  
Vol 19 (8) ◽  
pp. 825-836 ◽  
Author(s):  
V. Lehmann ◽  
G. Teschke
Keyword(s):  
Signal Processing ◽  
Radar Data ◽  
Parametric Estimation ◽  
Wind Profiler ◽  
Radio Science ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Wind Profiler Radar ◽  
Instruments And Techniques ◽  
Non Parametric Estimation

Abstract. In this paper, we apply wavelet thresholding for removing automatically ground and intermittent clutter (airplane echoes) from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which allow us to identify the coefficients relevant for clutter and to suppress them in order to obtain filtered reconstructions.Key words. Meteorology and atmospheric dynamics (instruments and techniques) – Radio science (remote sensing; signal processing)

scholarly journals COHERENT NOISE ATTENUATION USING THE WAVELET TRANSFORM ON RADIAL BASIS

2017 ◽  
Vol 34 (4) ◽  
Author(s):  
Lucas José Andrade de Almeida ◽  
Rafael Rodrigues Manenti ◽  
Milton J. Porsani
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Time Domain ◽  
Seismic Data ◽  
Seismic Noise ◽  
Noise Attenuation ◽  
Coherent Noise ◽  
Reflection Seismic ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

ABSTRACT. Radial transform rearranges amplitudes of seismic data, from distance-time domain to angle-time domain. Linear events in distance-time domain tend to e sampled as a vertical event in angle-time domain, while seismic...Keywords: reflection seismic, noise attenuation, signal processing, multi-resolution analysis. RESUMO. A transformada radial faz um remapeamento das amplitudes do dado sísmico do domínio espaço tempo para o domínio ângulo-tempo. Eventos lineares no primeiro domínio tendem...Palavras-chave: sísmica de reflexão, atenuação de ruídos, processamento de sinais, análise de multirresolução.

scholarly journals Aplikasi Wavelet Untuk Penghilangan Derau Isyarat Elektrokardiograf

2011 ◽  
Vol 2 (2) ◽  
Author(s):  
Bernardinus Sri Widodo
Keyword(s):  
Signal Processing ◽  
The Other ◽  
Optimum Level ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Selection Of

Abstract. Wavelet Application For Denoising Electrocardiograph Signal. Wavelet has the advantage of the ability to do multi resolution analysis in which one of its applications is to diminish noises. The major wavelet was selected and some experiments were conducted to find out the scale from 1 to 6. Furthermore, some other continuous experiments were carried out to determine the level of optimal decomposition and wavelet reconstruction. From the research, the findings showed that the selection of the scale from 1-6 did not influence the result significantly. On the other side, from the experiment of the selection of decomposition and reconstruction level, the eighth level was the most optimum level. The result of diminishing noises on the EKG signals using wavelet was slightly seen. From 48 data samples, the average of diminishing noises was 36.20 dB. Keywords: Signal Processing, Wavelet Application, ECG denoising   Abstrak. Wavelet memiliki keuntungan dari kemampuan untuk melakukan analisis multi-resolusi di mana salah satu aplikasi adalah untuk mengurangi suara. Wavelet utama adalah dipilih dan beberapa eksperimen dilakukan untuk mengetahui skala dari 1 sampai 6. Selain itu, beberapa percobaan kontinyu lainnya dilakukan untuk menentukan tingkat dekomposisi dan rekonstruksi wavelet yang optimal. Dari penelitian, temuan menunjukkan bahwa pemilihan skala 1-6 tidak mempengaruhi hasil secara signifikan. Di sisi lain, dari eksperimen pemilihan tingkat dekomposisi dan rekonstruksi, tingkat kedelapan tingkat yang paling optimal. Hasil suara mengurangi pada sinyal EKG menggunakan wavelet sedikit terlihat. Dari 48 sampel data, rata-rata suara berkurang adalah 36,20 dB. Kata Kunci: Pengolahan Sinyal, Aplikasi Wavelet, EKG denoising

scholarly journals Automated detection of satellite contamination in incoherent scatter radar spectra

2003 ◽  
Vol 21 (5) ◽  
pp. 1177-1182 ◽  
Author(s):  
J. Porteous ◽  
A. M. Samson ◽  
K. A. Berrington ◽  
I. W. McCrea
Keyword(s):  
Radar Data ◽  
Small Sample ◽  
Automated Detection ◽  
Incoherent Scatter Radar ◽  
Data Set ◽  
Radio Science ◽  
Incoherent Scatter ◽  
Scatter Radar ◽  
Radar Echoes ◽  
Instruments And Techniques

Abstract. Anomalous ion line spectra have been identified in many experiments. Such spectra are defined as deviations from the standard symmetric "double-humped" spectra derived from incoherent scatter radar echoes from the upper atmosphere. Some anomalous spectra – where there are sharp enhancements of power over restricted height ranges – have been attributed to satellite contamination in the beam path. Here we outline a method for detecting such contamination, and review in detail a few cases where the method enables the identification of anomalous spectra as satellite echoes, subsequently ascribed to specific orbital objects. The methods used here to identify such satellites provide a useful way of distinguishing anomalous spectra due to satellites from those of geophysical origin. Analysis of EISCAT Svalbard Radar data reveals that an average of 8 satellites per hour are found to cross the beam. Based on a relatively small sample of the data set, it appears that at least half of the occurrences of anomalous spectra are caused by satellite contamination rather than being of geophysical origin.Key words. Ionosphere (auroral ionosphere, instruments and techniques) – Radio Science (signal processing)

Analysis of relationship between wrinkle distribution and age based on the components of surface reflection by removing luminance unevenness on the face

2019 ◽  
Vol 2019 (1) ◽  
pp. 120-125
Author(s):  
Ikumi Nomura ◽  
Kaito Iuchi ◽  
Mihiro Uchida ◽  
Nobutoshi Ojima ◽  
Takeo Imai ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Signal Processing ◽  
Wavelet Transform ◽  
Multiresolution Analysis ◽  
Principal Component ◽  
Surface Reflection ◽  
Multi Resolution Analysis ◽  
The Face ◽  
Resolution Analysis ◽  
The Relationship

In this paper, we perform multi-resolution analysis by using Wavelet transform for the components of surface reflection on faces in order to acquire features of wrinkles and fine asperities on the face. Also, by applying principal component analysis to the acquired trend of the wrinkles and the fine asperities, we analyze the relationship between the distribution of wrinkles and asperities, and actual age statistically. In the previous researches, components of facial surface reflection were directly used for multiresolution analysis, and it is considered that the acquired relationship was dependent on the luminance unevenness of lighting on the face. In this research, therefore, we propose to remove the luminance unevenness of the lighting on the face is transformed into uniform distribution by signal processing, and it contributes to the appropriate analysis to the component of surface reflection on the face.

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