Mahdy Nabaee

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In this paper, we study joint network coding and distributed source coding of inter-node dependent messages, with the perspective of compressed sensing. Specifically, the theoretical guarantees for robust `1-min recovery of an under-determined set of linear network coded sparse messages are investigated. We discuss the guarantees for `1-min decoding of(More)
In this paper, we study the data gathering problem in the context of power grids by using a network of sensors, where the sensed data have inter-node redundancy. Specifically, we propose a new transmission method, called quantized network coding, which performs linear network coding in the infinite field of real numbers, and quantization to accommodate the(More)
Non-adaptive joint source network coding of correlated sources is discussed in this paper. By studying the information flow in the network, we propose quantized network coding as an alternative for packet forwarding. This technique has both network coding and distributed source coding advantages, simultaneously. Quantized network coding is a combination of(More)
Location information of sensor nodes has become an essential part of many applications in Wireless Sensor Networks (WSN). The importance of location estimation and object tracking has made them the target of many security attacks. Various methods have tried to provide location information with high accuracy, while lots of them have neglected the fact that(More)
In this paper, mathematical bases for non-adaptive joint source network coding of correlated messages in a Bayesian scenario are studied. Specifically, we introduce one-step Quantized Network Coding (QNC), which is a hybrid combination of network coding and packet forwarding for transmission. Motivated by the work on Bayesian compressed sensing, we derive(More)
This thesis concerns with recovery of compressive sampled images. Since many natural signals such as images are non-stationary, the sparse space varies in time/spatial domain. Therefore, compressive sensing (CS) recovery should be carried on locally adaptive, signal-dependent spaces to answer the fact that the CS measurements are not dependant to the signal(More)
Locating the license plate in the image is a key initial step in automatic License Plate Recognition via machine vision. This step becomes more complicated when the image scene is arbitrary (complex) and the view-angle of camera and luminance conditions are not calibrated and constant. In this paper, a new License Plate Detection method in complex scenes is(More)
In this paper, we discuss non-adaptive distributed compression of inter-node correlated real-valued messages. To do so, we discuss the performance of conventional packet forwarding via routing, in terms of the total network load versus the resulting quality of service (distortion level). As a better alternative for packet forwarding, we briefly describe our(More)