Xiaodong Bai
ABSTRACT
A method for obtaining the specific usage of spectrum in the power spectrum sequence is proposed in this paper. For the obtained power spectrum, baseline noise is fitted by the Fourier series and then subtracted from the original power spectrum signal value firstly. Afterwards, power spectrum was converted into an image and is further processed by the image-filtering method. More specifically, the image was mean-filtered with the appropriate window function template, and the filtered image was converted into a power spectrum by valuing on the abscissa. Finally, DBSCAN clustering is used to the processed spectrum to identify the specific use of the signal power spectrum. In the experiment, the proposed method was compared with the classic energy detection method. The results showed that proposed method could well restore the proposed of spectrum resources.
- Mitola J I, Maguire G Q J. Cognitive radio: making software radios more personal{J}. IEEE Pers Commun, 1999, 6(4):13--18.Google Scholar
Cross Ref
- ITU-R SM 1536.Frequency channel occupancy measurement.2001.Google Scholar
- Press WH, Teukolsky S, Vetterling WT, Flannery BP. 1995. Numerical recipies in C. Cambridge UK: Cambridge University Press.Google Scholar
- Breen EJ, Hopwood FG, Williams KL, Wilkins MR. 2000. Automatic poissonpeak harvesting for high throughput protein identification. Electrophoresis 21:2243--2251.Google Scholar
- Soille P. 2003. Morphological image analysis. Berlin: Springer Verlag. Google ScholarDigital Library
- Coombes KR, Fritsche HA, Clarke C, Chen JN, et al. 2003. Quality control and peak find for proteomics data collected from nipple aspirate fluid by surfaceenhanced laser desorption and ionization. Clin Chem 49:1615--1623.Google ScholarCross Ref
- Zhang P, Li F. A New Adaptive Weighted Mean Filter for Removing Salt-and-Pepper Noise{J}. IEEE Signal Processing Letters, 2014, 21(10):1280--1283.Google ScholarCross Ref
- Gonzalez R C, Woods R E. Digital image processing{J}. Prentice Hall International, 2008, 28(4):484--486. Google ScholarDigital Library
- Brendan J. Frey; Delbert Dueck (2007). "Clustering by passing messages between data points". Science. 315 (5814): 972--976.Google Scholar
- Ester, Martin; Kriegel, Hans-Peter; Sander, Jörg; Xu, Xiaowei (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96). AAAI Press. pp. 226--231. Google ScholarDigital Library
- DBSCAN Schubert, Erich; Sander, Jörg; Ester, Martin; Kriegel, Hans Peter; Xu, Xiaowei (2017). "DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN". ACM Trans. Database Syst. 42 (3): 19:1--19:21. Google ScholarDigital Library
Index Terms
- Identification Method of Power Spectral Signal Based on Fourier Series Fitting and Density Clustering
Recommendations
Representation of the Fourier Transform by Fourier Series
The analysis of the mathematical structure of the integral Fourier transform shows that the transform can be split and represented by certain sets of frequencies as coefficients of Fourier series of periodic functions in the interval $$[0,2\pi)$$ . In this paper we ...
Signal reconstruction from two close fractional Fourier power spectra
Based on the definition of the instantaneous frequency (signal phase derivative) as a local moment of the Wigner distribution, we derive the relationship between the instantaneous frequency and the derivative of the squared modulus of the fractional ...
Algorithm 338: algol procedures for the fast Fourier transform
The following procedures are based on the Cooley-Tukey algorithm [1] for computing the finite Fourier transform of a complex data vector; the dimension of the data vector is assumed here to be a power of two. Procedure COMPLEXTRANSFORM computes either ...
Comments