Alireza Pourafzal

Alireza Pourafzal
Norwegian University of Science and Technology | NTNU · Faculty of Engineering

Master of Sciences in Telecommunication Systems

About

18
Publications
737
Reads
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5
Citations
Citations since 2017
18 Research Items
5 Citations
2017201820192020202120222023024681012
2017201820192020202120222023024681012
2017201820192020202120222023024681012
2017201820192020202120222023024681012
Education
September 2016 - February 2019
Khaje Nasir Toosi University of Technology
Field of study
  • Telecommunication Systems Engineering
September 2012 - September 2016
Khaje Nasir Toosi University of Technology
Field of study
  • Electrical Engineering

Publications

Publications (18)
Article
A novel low-cost microwave sensor system is proposed for accurate sensing of the real relative permittivity of materials under test (MUT). The proposed solution eliminates the need for using advanced measurement devices such as the vector network analyzer (VNA) for sensor characterization. The proposed sensor system is built on a software-defined r...
Article
Full-text available
A deep learning method is developed for chaotic time series classification. We investigate the chaotic state of a dynamical system, based on the output of the system. One of the main obstacles in time series classification is mapping a high-dimensional vector into a scalar value. To reduce the dimensions, it is common to use an average pooling laye...
Article
Full-text available
In this work, a hybrid radio frequency (RF)- and acoustic-based activity recognition system was developed to demonstrate the advantage of combining two non-invasive sensors in Human Activity Recognition (HAR) systems and smart assisted living. We used a hybrid approach, employing RF and acoustic signals to recognize falling, walking, sitting on a c...
Conference Paper
Full-text available
In this paper, the problem of entropy-based classification of time-series into stochastic, chaotic, and periodic is addressed, followed by proposing an alternative joint-entropy approach to time series classification. These data-driven methods describe the behavior of a signal, using the association of the entropy of a time-series with emergence an...
Conference Paper
Full-text available
In this paper, a more accurate diagonal approximation of the covariance matrix in the frequency domain is investigated. For this purpose, First, the frequency snapshot model approximation is revised and the imposed error between the approximated and true value is formulated. Then, by using Taylor series, the problem of inverse matrix approximation...
Conference Paper
Full-text available
Chaotic behavior may be observed in many natural and human-made time series, thus one of the first things to acquire is the knowledge on their chaotic behavior. Several approaches including model-based and data-driven classifications are utilized to address this issue; however, the computational burden arisen with the higher performance seems to be...

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Projects

Projects (2)
Archived project
The goal of this project is to set a line to detect the difference between chaotic, stochastic and periodic time series.
Archived project
I'm working on radar waveform design to optimize the probability of detection.