University of Montenegro
Srdjan Stankovic mostly deals with Time–frequency analysis, Algorithm, Signal processing, Fourier transform and Artificial intelligence. The concepts of his Time–frequency analysis study are interwoven with issues in Instantaneous phase and Speech recognition. Srdjan Stankovic interconnects Digital signal processing and Frequency domain in the investigation of issues within Algorithm.
His studies in Signal processing integrate themes in fields like Floating point, Estimator, Electronic engineering and Spectrogram. His research in Artificial intelligence intersects with topics in Radar, Computer vision and Pattern recognition. His studies deal with areas such as Reconstruction algorithm, Signal, Small set and Compressed sensing as well as Pattern recognition.
The scientist’s investigation covers issues in Algorithm, Compressed sensing, Time–frequency analysis, Signal and Artificial intelligence. His work carried out in the field of Algorithm brings together such families of science as Spectrogram, Representation, Fourier transform and Signal processing. Srdjan Stankovic combines subjects such as Signal reconstruction, Noise, Reconstruction algorithm, Mathematical optimization and Inverse synthetic aperture radar with his study of Compressed sensing.
His Time–frequency analysis research is multidisciplinary, incorporating perspectives in Estimation theory, Speech recognition, Frequency domain, Instantaneous phase and Electronic engineering. His Signal research is multidisciplinary, relying on both Wireless, Basis, Missing data and Hermite polynomials. Srdjan Stankovic has included themes like Computer vision and Pattern recognition in his Artificial intelligence study.
Srdjan Stankovic spends much of his time researching Compressed sensing, Algorithm, Signal, Signal reconstruction and Artificial intelligence. His Compressed sensing research includes themes of Time–frequency analysis, Noise, Gradient based algorithm, Signal processing and Electronic engineering. Many of his studies on Time–frequency analysis apply to Speech recognition as well.
Srdjan Stankovic integrates Algorithm with Domain in his research. His Signal research incorporates themes from Representation, Mathematical optimization, Missing data and Speedup. The Artificial intelligence study combines topics in areas such as Machine learning, Computer vision and Pattern recognition.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Decentralized Parameter Estimation by Consensus Based Stochastic Approximation
S S Stanković;M S Stankovic;D M Stipanovic.
IEEE Transactions on Automatic Control (2011)
Digital watermarking in the fractional Fourier transformation domain
Igor Djurovic;Srdjan Stankovic;Ioannis Pitas.
Journal of Network and Computer Applications (2001)
Watermarking in the space/spatial-frequency domain using two-dimensional Radon-Wigner distribution
S. Stankovic;I. Djurovic;I. Pitas.
IEEE Transactions on Image Processing (2001)
Fast communication: Missing samples analysis in signals for applications to L-estimation and compressive sensing
Ljubisa Stankovic;Srdjan Stankovic;Moeness Amin.
Signal Processing (2014)
Separation of target rigid body and micro-doppler effects in ISAR imaging
S. Stankovic;I. Djurovic;T. Thayaparan.
IEEE Transactions on Aerospace and Electronic Systems (2006)
Compressive Sensing Based Separation of Nonstationary and Stationary Signals Overlapping in Time-Frequency
Ljubisa Stankovic;Irena Orovic;Srdjan Stankovic;Moeness Amin.
IEEE Transactions on Signal Processing (2013)
Multimedia Signals and Systems
Srdjan Stankovic;Irena Orovic;Ervin Sejdic.
Instantaneous frequency in time–frequency analysis: Enhanced concepts and performance of estimation algorithms
Ljubiša Stanković;Igor Djurović;Srdjan Stanković;Marko Simeunović.
Digital Signal Processing (2014)
Fast communication: An automated signal reconstruction method based on analysis of compressive sensed signals in noisy environment
Srdjan Stanković;Irena Orović;Ljubiša Stanković.
Signal Processing (2014)
Local polynomial Fourier transform: A review on recent developments and applications
Xiumei Li;Guoan Bi;Srdjan Stankovic;Abdelhak M. Zoubir.
Signal Processing (2011)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: