Metrika članka

  • citati u SCindeksu: 0
  • citati u CrossRef-u:[1]
  • citati u Google Scholaru:[=>]
  • posete u prethodnih 30 dana:3
  • preuzimanja u prethodnih 30 dana:3
članak: 1 od 1  
Telfor Journal
2017, vol. 9, br. 2, str. 92-97
jezik rada: engleski
vrsta rada: neklasifikovan
doi:10.5937/telfor1702092B


Sparse representation of FHSS signals in the Hermite transform domain
(naslov ne postoji na srpskom)
Faculty of Electrical Engineering, University of Montenegro, Podgorica, Montenegro

e-adresa: andjelad@ac.me

Projekat

Project of the Montenegrin Ministry of Science: 'New ICT Compressive sensing based trends applied to: Multimedia, biomedicine and communications'

Sažetak

(ne postoji na srpskom)
Signal sparsity is exploited in various signal processing approaches. Signal compression, classification, coding, as well as the recently introduced compressed sensing are some examples where the possibility to represent a signal sparsely determines the efficiency of the applied processing technique. However, the possibility of a sparse signal representation in a transform basis is highly dependent on the signal nature. Therefore, finding a suitable basis where the signal exhibits a compact support is a challenging task. In this paper, the Hermite Transform (HT) is considered as a sparsity domain for the FHSS wireless communication signals. The transform coefficients sparsification is done by optimizing the scaling factor and time-shift of basis functions. The optimization is done by minimizing the concentration measure of HT coefficients. The theory is verified by numerical examples with synthetic FHSS signals.

Ključne reči

FHSS signals; signal sparsity; sparsification; Hermite transform domain

Reference

Berder, O., Bouder, C., Burel, G. (2000) Identification of frequency hopping communications. u: Problems in Modern App. Mathem, WSES, pp. 259-264, ISBN 960 8052-15-7
Brajovic, M., Orovic, I., Stankovic, S. (2016) The Optimization of the Hermite transform: Application perspectives and 2D generalization. u: 2016 24th Telecommunications Forum (TELFOR), Institute of Electrical and Electronics Engineers (IEEE), str. 1-4
Brajovic, M., Draganic, A., Orovic, I., Stankovic, S. (2016) FHSS signal sparsification in the Hermite transform domain. u: 2016 24th Telecommunications Forum (TELFOR), Institute of Electrical and Electronics Engineers (IEEE), str. 1-4
Brajović, M., Daković, M., Orović, I., Stanković, S. (2016) Gradient-based signal reconstruction algorithm in Hermite transform domain. Electronics Letters, 52(1): 41-43
Brajović, M., Orović, I., Daković, M., Stanković, S. (2017) On the parameterization of Hermite transform with application to the compression of QRS complexes. Signal Processing, 131: 113-119
Carrillo, R.E., Barner, K.E., Aysal, T.C. (2010) Robust Sampling and Reconstruction Methods for Sparse Signals in the Presence of Impulsive Noise. IEEE Journal of Selected Topics in Signal Processing, 4(2): 392-408
Draganic, A., Orovic, I., Stankovic, S. (2013) FHSS signal characterization based on the crossterms free time-frequency distributions. u: 2013 2nd Mediterranean Conference on Embedded Computing (MECO), Institute of Electrical and Electronics Engineers (IEEE), str. 152-155
Elad, M. (2010) Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing. Springer
Gandetto, M., Guainazzo, M., Regazzoni, C.S. (2004) Use of Time-Frequency Analysis and Neural Networks for Mode Identification in a Wireless Software-Defined Radio Approach. EURASIP Journal on Advances in Signal Processing, 2004(12):
Klemens, G. (2010) The cellphone: The history and technology of the gadget that changed the world. McFarland, Sept
Krylov, A., Korchagin, D. (2006) Fast Hermite Projection Method. Berlin, Heidelberg: Springer Nature, str. 329-338
Ma, R., Shi, L., Huang, Z., Zhou, Y. (2014) EMP Signal Reconstruction Using Associated-Hermite Orthogonal Functions. IEEE Transactions on Electromagnetic Compatibility, 56(5): 1242-1245
Martens, J.-B. (1990) The Hermite transform-theory. IEEE Transactions on Acoustics, Speech, and Signal Processing, 38(9): 1595-1606
Marvasti, F., Amini, A., Haddadi, F., Soltanolkotabi, M., Khalaj, B., Aldroubi, A., Sanei, S., Chambers, J. (2012) A unified approach to sparse signal processing. EURASIP Journal on Advances in Signal Processing, 2012(1): 44
Mengtao, Y., de A., Sarkar, T.K., Jinhwan, K., Baek, H.J. (2006) Conditions for generation of stable and accurate hybrid TD-FD MoM solutions. IEEE Transactions on Microwave Theory and Techniques, 54(6): 2552-2563
Orović, I., Papić, V., Ioana, C., Li, X., Stanković, S. (2016) Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations. Mathematical Problems in Engineering, 2016: 1-16
Orović, I., Stanković, S., Draganić, A. (2015) Sparse time-frequency representation for signals with fast varying instantaneous frequency. IET Radar, Sonar & Navigation, 9(9): 1260-1267
Pickholtz, R., Schilling, D., Milstein, L. (1982) Theory of Spread-Spectrum Communications - A Tutorial. IEEE Transactions on Communications, 30(5): 855-884
Rasiah, A.I., Togneri, R., Attikiouzel, Y. (1997) Modelling 1-D signals using Hermite basis functions. IEE Proceedings - Vision, Image, and Signal Processing, 144(6): 345
Sandryhaila, A., Saba, S., Puschel, M., Kovacevic, J. (2012) Efficient Compression of QRS Complexes Using Hermite Expansion. IEEE Transactions on Signal Processing, 60(2): 947-955
Stankovic, S., Orovic, I., Sejdic, E. (2012) Multimedia Signals and Systems. New York: Springer
Stanković, S., Orović, I., Krylov, A. (2010) Two-dimensional Hermite S-method for high-resolution inverse synthetic aperture radar imaging applications. IET Signal Processing, 4(4): 352
Stankovic, S., Orovic, I., Mobasseri, B., Chabert, M. (2012) A Robust Procedure for Image Watermarking based on the Hermite Projection Method. Automatika ‒ Journal for Control, Measurement, Electronics, Computing and Communications, 53(4):
Stanković, S., Orović, I. (2014) Improved higher order robust distributions based on compressive sensing reconstruction. IET Signal Processing, 8(7): 738-748
Stanković, S., Stanković, L., Orović, I. (2015) Compressive Sensing Approach in the Hermite Transform Domain. Mathematical Problems in Engineering, 2015: 1-9