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Mangal Prakash

Publications and source records attributed to Mangal Prakash.

22 records · Page 2Linked to original sources

Fully Unsupervised Probabilistic Noise2Void

Image denoising is the first step in many biomedical image analysis pipelines and Deep Learning (DL) based methods are currently best performing. A new category of DL methods such as Noise2Void or Noise2Self can be used fully unsupervised, requiring nothing but the noisy data. However, this comes at the price of reduced reconstruction quality. The recently proposed Probabilistic Noise2Void (PN2V) improves results, but requires an additional noise model for which calibration data needs to be acquired. Here, we present improvements to PN2V that (i) replace histogram based noise models by parametric noise models, and (ii) show how suitable noise models can be created even in the absence of calibration data. This is a major step since it actually renders PN2V fully unsupervised. We demonstrate that all proposed improvements are not only academic but indeed relevant.

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Distributed Apportioning in a Power Network for providing Demand Response Services

Greater penetration of Distributed Energy Resources (DERs) in power networks requires coordination strategies that allow for self-adjustment of contributions in a network of DERs, owing to variability in generation and demand. In this article, a distributed scheme is proposed that enables a DER in a network to arrive at viable power reference commands that satisfies the DERs local constraints on its generation and loads it has to service, while, the aggregated behavior of multiple DERs in the network and their respective loads meet the ancillary services demanded by the grid. The Net-load Management system for a single unit is referred to as the Local Inverter System (LIS) in this article . A distinguishing feature of the proposed consensus based solution is the distributed finite time termination of the algorithm that allows each LIS unit in the network to determine power reference commands in the presence of communication delays in a distributed manner. The proposed scheme allows prioritization of Renewable Energy Sources (RES) in the network and also enables auto-adjustment of contributions from LIS units with lower priority resources (non-RES). The methods are validated using hardware-in-the-loop simulations with Raspberry PI devices as distributed control units, implementing the proposed distributed algorithm and responsible for determining and dispatching realtime power reference commands to simulated power electronics interface emulating LIS units for demand response.

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Distributed Finite Time Termination of Consensus in the Presence of Delays

Linear consensus iterations guarantee asymptotic convergence, thereby, limiting their applicability in applications where consensus value needs to be used in real time to perform a system level task. It also leads to wastage of power and communication resources. In this article, an algorithm is proposed which enables each node to detect in a distributed manner and in finite number of iterations, when every agent in the network is within a user specified threshold of the consensus value (approximate consensus) and hence terminate further communications and computations associated with consensus iterations. This article develops a distributed algorithm for achieving this approximate consensus in presence of random time-varying bounded communication delays. Moreover, the article instantiates the algorithm developed to distributively determine the average of the initial values held by agents in finite number of iterations. Specifically, this algorithm relies on distributively determining the maximum and minimum of values held by the agents. The approach presented here offers several advantages, including reduced computational complexity, and hence, is suited for hardware implementation. An experimental test bed of Raspberry-Pi agents that communicate wirelessly over neighborhoods is employed as a platform to demonstrate the effectiveness of the developed algorithm.

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Distributed Finite Time Termination of Ratio Consensus for Averaging in the presence of Delays

Distributed averaging of agent initial conditions is a well-studied problem in context of networked systems where coordination amongst the agents is of paramount importance. The asymptotic nature of convergence of distributed averaging protocols and presence of communication delays, however, makes it challenging to implement in practical settings. It is important that agents develop the ability to detect on their own when average of the initial conditions of the agents is achieved within some pre-specified tolerance and stop further computations to avoid overhead expenses in the presence of delays. This article presents a distributed finite time stopping criterion for distributed averaging using ratio consensus on a fixed interconnection topology. The practical utility of the algorithm has been illustrated through simulations.

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