37 citations · 78 across the 15 of their papers we have counts for
17 papers
On the Practical Performance of Noise Modulation for Ultra-Low-Power IoT: Limitations, Capacity, and Energy Trade-offs
Felipe A. P. de Figueiredo, Pedro M. R. Pereira, Evandro C. Vilas Boas +3
Ultra-low-power (ULP) Internet of Things (IoT) applications demand communication architectures with minimal energy consumption. Noise Modulation (NoiseMod) addresses this by encodi…
Bayesian Convolutional Neural Networks for Prior Learning in Graph Signal Recovery
Razieh Torkamani, Arash Amini, Hadi Zayyani +1
Graph signal recovery (GSR) is a fundamental problem in graph signal processing, where the goal is to reconstruct a complete signal defined over a graph from a subset of noisy or m…
Markovian Block Sparse Signal Detection Using One Bit Measurements
Alireza Hariri, Hadi Zayyani, Mehdi Korki
This paper presents a novel sparse signal detection scheme designed for a correlated Markovian Bernoulli-Gaussian sparse signal model, which can equivalently be viewed as a block s…
Double-Private Distributed Estimation Algorithm Using Differential Privacy and a Key-Like Proportionate Matrix with Its Performance Analysis
Mehdi Korki, Fatemehsadat Hosseiniamin, Hadi Zayyani +1
In this brief, we present an enhanced privacy-preserving distributed estimation algorithm, referred to as the ``Double-Private Algorithm," which combines the principles of both dif…
Second-Order Nonlinearity Estimated and Compensated Diffusion LMS Algorithm: Theoretical Upper Bound, Cramer-Rao Lower bound, and Convergence Analysis
Hadi Zayyani, Mehdi Korki
In this paper, an algorithm for estimation and compensation of second-order nonlinearity in wireless sensor setwork (WSN) in distributed estimation framework is proposed. First, th…
Proportionate Adaptive Graph Signal Recovery
Razieh Torkamani, Hadi Zayyani, Mehdi Korki
This paper generalizes the proportionate-type adaptive algorithm to the graph signal processing and proposes two proportionate-type adaptive graph signal recovery algorithms. The g…
Robust Adaptive Generalized Correntropy-based Smoothed Graph Signal Recovery with a Kernel Width Learning
Razieh Torkamani, Hadi Zayyani, Farokh Marvasti
This paper proposes a robust adaptive algorithm for smooth graph signal recovery which is based on generalized correntropy. A proper cost function is defined for this purpose. The…
Statistical Graph Signal Recovery Using Variational Bayes
Razieh Torkamani, Hadi Zayyani
This paper investigates the problem of graph signal recovery (GSR) when the topology of the graph is not known in advance. In this paper, the elements of the weighted adjacency mat…
One Bit Spectrum Sensing in Cognitive Radio Sensor Networks
Hadi Zayyani, Farzan Haddadi, Mehdi Korki
This paper proposes a spectrum sensing algorithm from one bit measurements in a cognitive radio sensor network. A likelihood ratio test (LRT) for the one bit spectrum sensing probl…
Weighted diffusion LMP algorithm for distributed estimation in non-uniform noise conditions
H. Zayyani, M. Korki
This letter presents an improved version of diffusion least mean ppower (LMP) algorithm for distributed estimation. Instead of sum of mean square errors, a weighted sum of mean squ…
Double-detector for Sparse Signal Detection from One Bit Compressed Sensing Measurements
Hadi Zayyani, Farzan Haddadi, Mehdi Korki
This letter presents the sparse vector signal detection from one bit compressed sensing measurements, in contrast to the previous works which deal with scalar signal detection. In…
Non-Coherent Direction of Arrival Estimation via Frequency Estimation
Hadi Zayyani, Mehdi Korki
This letter investigates the non-coherent Direction of Arrival (DOA) estimation problem dealing with the DOA estimation from magnitude only measurements of the array output. The ma…
Sparse Diffusion Steepest-Descent for One Bit Compressed Sensing in Wireless Sensor Networks
Hadi Zayyani, Mehdi Korki, Farrokh Marvasti
This letter proposes a sparse diffusion steepest-descent algorithm for one bit compressed sensing in wireless sensor networks. The approach exploits the diffusion strategy from dis…
Bayesian hypothesis testing for one bit compressed sensing with sensing matrix perturbation
H. Zayyani, M. Korki, F. Marvasti
This letter proposes a low-computational Bayesian algorithm for noisy sparse recovery in the context of one bit compressed sensing with sensing matrix perturbation. The proposed al…
Dictionary Learning for Blind One Bit Compressed Sensing
Hadi Zayyani, Mehdi Korki, Farrokh Marvasti
This letter proposes a dictionary learning algorithm for blind one bit compressed sensing. In the blind one bit compressed sensing framework, the original signal to be reconstructe…
Bayesian Hypothesis Testing for Block Sparse Signal Recovery
Mehdi Korki, Hadi Zayyani, Jingxin Zhang
This letter presents a novel Block Bayesian Hypothesis Testing Algorithm (Block-BHTA) for reconstructing block sparse signals with unknown block structures. The Block-BHTA comprise…
Iterative Bayesian Reconstruction of Non-IID Block-Sparse Signals
Mehdi Korki, Jingxin Zhang, Cishen Zhang +1
This paper presents a novel Block Iterative Bayesian Algorithm (Block-IBA) for reconstructing block-sparse signals with unknown block structures. Unlike the existing algorithms for…