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We address for the first time the question of how networked agents can collaboratively fit a Morozov-regularized linear model when each agent knows a summand of the regression data. This question generalizes previously studied data-splitting scenarios, which require that the data be partitioned among the agents. To answer the question, we introduce a class of network-structured problems, which contains the regularization problem, and by using the Douglas-Rachford splitting algorithm, we develop a distributed algorithm to solve these problems.

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In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how the Randomized Block Kaczmarz (RBK) method—a method for solving linear systems—works as gossip algorithm when applied to a special system encoding the underlying network. The famous pairwise gossip algorithm arises as a special case.

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In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how the Randomized Block Kaczmarz (RBK) method—a method for solving linear systems—works as gossip algorithm when applied to a special system encoding the underlying network. The famous pairwise gossip algorithm arises as a special case.

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8 Views

In this short note we propose a new approach for the design and analysis of randomized gossip algorithms which can be used to solve the average consensus problem. We show how the Randomized Block Kaczmarz (RBK) method—a method for solving linear systems—works as gossip algorithm when applied to a special system encoding the underlying network. The famous pairwise gossip algorithm arises as a special case.

Categories:
10 Views

The construction of complementary sets of unimodular sequences of length N, with low correlation and complementary correlation coefficients is addressed. The design criterion is based on the minimisation of a cost function that penalizes the integrated side lobe as well as the sum of the complementary correlations of the sequences in the set. Numerical solution to the proposed cost function is obtained using conventional optimization methods.

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12 Views

Extracting the Electric Network Frequency (ENF) fluctuations from an audio recording and comparing it to a reference database is a new approach in performing forensic digital audio authentication. The problem statement of the IEEE SP cup 2016 competition relates to time-varying location-dependent signature of power grids as it becomes intrinsically captured in media recordings, due to direct or indirect influences from the respective power grid. In this project signal processing and information security/forensics are collectively elaborated.

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This paper presents methods to analyze functional brain networks and signals from graph spectral perspectives. The notion of frequency and filters traditionally defined for signals supported on regular domains such as discrete time and image grids has been recently generalized to irregular graph domains, and defines brain graph frequencies associated with different levels of spatial smoothness across the brain regions. Brain network frequency also enables the decomposition of brain signals into pieces corresponding to smooth or rapid variations.

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44 Views

In this work, a directional modulation-based technique is devised to enhance the security of a multi-antenna wireless communication system employing M-PSK modulation to convey information. The directional modulation method operates by steering the array beam in such a way that the phase of the received signal at the receiver matches that of the intended M-PSK symbol. Due to the difference between the channels of the legitimate receiver and the eavesdropper, the signals received by the eavesdropper generally encompass a phase component different than the actual symbols.

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