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Digital Signature Schemes
Published in Jonathan Katz, Yehuda Lindell, Introduction to Modern Cryptography, 2020
An identification scheme is an interactive protocol that allows one party to prove its identity (i.e., to authenticate itself) to another. This is a very natural notion, and it is common nowadays to authenticate oneself when logging in to a website. We call the party identifying herself (e.g., the user) the “prover,” and the party verifying the identity (e.g., the web server) the “verifier.” Here, we are interested in the public-key setting where the prover and verifier do not share any secret information (such as a password) in advance; instead, the verifier only knows the public key of the prover. Successful execution of the identification protocol convinces the verifier that it is communicating with the intended prover rather than an imposter.
Simultaneous identification and optimal tracking control of unknown continuous-time systems with actuator constraints
Published in International Journal of Control, 2021
Amardeep Mishra, Satadal Ghosh
Various online parameter update schemes for identifiers have been presented in the literature like minimisation of the residual identifier output error in Zhang et al. (2011), modified robust integral of sign of the error (RISE) algorithm in Bhasin et al. (2013), experience replay (ER)-based method in Modares et al. (2013), etc. However, in all the aforementioned papers, it was desired to achieve the identifier state to converge to actual state x, while convergence of estimated weights to true weights was not guaranteed. As a remedy to this problem, a promising online identification method that ensured convergence to true NN weights based on the weights error, instead of state error, was proposed in Lv et al. (2016). An ER-based augmented version of the identifier update law in Lv et al. (2016) is now presented in this section. Note that the update law presented here has additional advantages compared to the one developed in Lv et al. (2016), for instance, ER leads to efficient utilisation of the past observations in learning NN weights. It should be noted here that the ER-based identification scheme presented in Modares et al. (2013) is different from the one in this paper in the sense that in Modares et al. (2013) error between actual state of the system and identifier state was minimised, whereas, in this paper the error between estimated and ideal identifier NN weights is minimised.
An improved identification and control of 3 × 3 multi-input multi-output system using relay and subspace method
Published in Indian Chemical Engineer, 2019
D. Kishore, Sethi Smruti Rajan, K. Anand Kishore, Rames C. Panda
Using the above two-step method, parameters of the system can be estimated. After estimating the parameters of the system by N4SID, the model is formulated. The mathematical model is used to generate response/output for arbitrary input data, thus generating input/output data. This input/output data set is considered as real-time data which may be used as input to identification scheme by relay feedback.
Estimation of characteristic vortex structures in complex flow
Published in Journal of Turbulence, 2021
Kaustav Chaudhury, Chandranath Banerjee, Swapnil Urankar
Various threshold-based local vortex identification schemes are available in the literature. However, the specific isovalues of these parameters to construct the vortex region remain unclear. Often, one has to choose the isovalue on a trial and test basis. The present study provides a set of sufficient criteria for selecting isovalue to construct the vortex region using a threshold-based local vortex identification scheme. The criteria are detailed in Section 3. The applications of these criteria are demonstrated in Section 4. A summary of the proposed criteria is presented below. While ω defines swirling strength, the relative importance of σ and ω signifies orbital compactness in a vortex region. Therefore, defining a vortex region based on the enhanced swirling criterion, i.e. using both σ and ω, seems to be a powerful paradigm.The JPDF on the plane of , i.e. the complex plane, can provide a diagrammatic understanding of different flow regimes. The correspondence between the flow regimes in the popular Q−R space and that in the complex plane is shown here. The JPDF on the complex plane is the key step to extract the characteristic vortex region, as we have shown here.One should also focus on the MPDFs of σ and ω, in addition to the JPDF. This approach enables us to focus on the concentration of swirling strength and orbital compactness in terms of the peaks in the corresponding MPDFs. One can select an isovalue of either σ or ω around the corresponding MPDF peaks. It is then highly likely that one may extract the characteristic vortex region that contains the essential features of the flow field.