Source identification and manipulation in stereo music recordings using frequency‐domain signal processing

2004 ◽  
Vol 115 (5) ◽  
pp. 2494-2494
Author(s):  
Carlos Avendano
Keyword(s):  
Signal Processing ◽  
Frequency Domain ◽  
Source Identification ◽  
Music Recordings

A High Efficient Baseband GNSS Signal Narrow Band Anti-Jamming Approach in Frequency Domain

2014 ◽  
Vol 926-930 ◽  
pp. 1857-1860
Author(s):  
Zhou Zheng ◽  
Meng Yuan Li ◽  
Wei Jiang Wang
Keyword(s):  
Signal Processing ◽  
Frequency Domain ◽  
Narrow Band ◽  
Low Frequency ◽  
Frequency Resolution ◽  
Interference Rejection ◽  
High Efficient ◽  
Digital Down Conversion ◽  
Down Conversion ◽  
Low Rate

In order to reduce the burden of the calculation and the low frequency resolution of the tradition GNSS signal intermediate narrow band anti-jamming method, it introduces a high efficient approach of narrow band interference rejection based on baseband GNSS signal processing. After digital down conversion to baseband and down sampling to a low rate, the interference is removed in frequency domain. According to the theoretical analysis and simulation, it claims that the method can reduce the calculation and increase the detection resolution in frequency domain which will realize a high efficient interference rejection.

scholarly journals The effect of temperature and frequency on magnetic properties of the Fe81B13Si4C2 amorphous alloy

2011 ◽  
Vol 43 (2) ◽  
pp. 175-182 ◽  
Author(s):  
S. Djukic ◽  
V. Maricic ◽  
A. Kalezic-Glisovic ◽  
L. Ribic-Zelenovic ◽  
S. Randjic ◽  
...  
Keyword(s):  
Signal Processing ◽  
Magnetic Properties ◽  
Amorphous Alloy ◽  
Frequency Domain ◽  
Magnetic Permeability ◽  
Structural Relaxation ◽  
Substantial Reduction ◽  
Effect Of Temperature ◽  
Influence Of Temperature ◽  
Mean Frequency

In this study it was investigated influence of temperature and frequency on permeability, coercivity and power loses of Fe81B13Si4C2 amorphous alloy. Magnetic permeability measurements performed in nonisothermal and isothermal conditions was confirmed that efficient structural relaxation was occurred at temperature of 663 K. This process was performed in two steps, the first one is kinetic and the second one is diffuse. Activation energies of these processes are: Ea1 = 52.02 kJ/mol for kinetic and Ea2 = 106.9 kJ/mol for diffuse. It was shown that after annealing at 663 K coercivity decrease about 30% and therefore substantial reduction in power loses was attained. Investigated amorphous alloy satisfied the criteria for signal processing devices that work in mean frequency domain.

scholarly journals Signal-Processing Framework for Ultrasound Compressed Sensing Data: Envelope Detection and Spectral Analysis

2020 ◽  
Vol 10 (19) ◽  
pp. 6956
Author(s):  
Yisak Kim ◽  
Juyoung Park ◽  
Hyungsuk Kim
Keyword(s):  
Signal Processing ◽  
Compressed Sensing ◽  
Frequency Domain ◽  
Time Domain ◽  
Sampling Rate ◽  
Processing Technique ◽  
Original Form ◽  
Basis Matrix ◽  
Full Reconstruction ◽  
Processing Framework

Acquisition times and storage requirements have become increasingly important in signal-processing applications, as the sizes of datasets have increased. Hence, compressed sensing (CS) has emerged as an alternative processing technique, as original signals can be reconstructed using fewer data samples collected at frequencies below the Nyquist sampling rate. However, further analysis of CS data in both time and frequency domains requires the reconstruction of the original form of the time-domain data, as traditional signal-processing techniques are designed for uncompressed data. In this paper, we propose a signal-processing framework that extracts spectral properties for frequency-domain analysis directly from under-sampled ultrasound CS data, using an appropriate basis matrix, and efficiently converts this into the envelope of a time-domain signal, avoiding full reconstruction. The technique generates more accurate results than the traditional framework in both time- and frequency-domain analyses, and is simpler and faster in execution than full reconstruction, without any loss of information. Hence, the proposed framework offers a new standard for signal processing using ultrasound CS data, especially for small and portable systems handling large datasets.

A Broadband Array Signal Processing Method Based on Joint Sparsity of Signal Spatial Domain

2019 ◽  
Author(s):  
Daqian He ◽  
Dahai Zhang ◽  
Congying Wang ◽  
Xirui Peng
Keyword(s):  
Signal Processing ◽  
Frequency Domain ◽  
Acoustic Signal ◽  
Array Signal Processing ◽  
Doa Estimation ◽  
Spatial Domain ◽  
Processing Method ◽  
Arrival Angle ◽  
Joint Sparsity ◽  
Signal Processing Method

Abstract Broadband underwater acoustic signal direction of arrival (DOA) estimation method is an important part of underwater array signal processing. The commonly used array signal DOA estimation algorithms due to the restriction of algorithm principles, are unable to process broadband array signal effectively, at the case of the arriving signals have strong correlation, small sampling snapshots or small arrival angle. Therefore, we need a new efficient algorithm to meet the increasing demand of broadband under water acoustic signal processing method. This paper makes use of the broadband acoustic signal similarity of joint sparsity in signal spatial domain received by underwater sonar arrays, establishes the whole space grid covering all broadband frequency domain slices. On the basis, the global sparsity of each frequency domain slice is combined with sparse element extraction class algorithm. By integrating the energy of signal on each slice, the spatial sparsity of each slice is obtained, from which we can get the directions of the arriving broadband wave signals. Through the simulation analysis and experimental verification on lake, we can be see that: The SDJS algorithm improves the performance and signal processing capability of the algorithm compared with the traditional algorithms. Therefore SDJS algorithm has a widely range of research value and application space.

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