A delta‐method technique in the wavelet domain to determine statistical quantities of the response of electromagnetic devices with uncertain parameters

Abstract

In this paper a method to determine the mean value and the variance of the response of a system with uncertain parameters is proposed. With the term 'response of a system' we indicate either the value of a single parameter that represents a figure of merit of a device (e.g. the efficiency of a transmission system or the band width of a communication channel) or a characteristic function of the system (e.g. the impulse or the frequency response). In the latter case we estimate the mean value and the variance at every sample of the response. The estimate is performed by using the delta method, a technique for approximating expected values of functions of random variables when the direct evaluation is not feasible. Two examples of the application of the proposed procedure are reported and the results are compared with simulations performed by a Monte Carlo analysis

Efficient worst‐case analysis of electronic networks in intervals of frequency

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“…There has been a lot of effort from the scientific community to tackle the problem of uncertainty analysis in electrical engineering, as it can be verified by the growing number of publications in this field …”

An optimized novel public cloud system to secure the medical record from third parties

“…Hence, cryptography is the familiar aspect of the cloud model to protect medical data against harmful attacks 3 . However, this model has met several problems because of the crypto algorithm's extensive data and slow key generation model 4 . This has the potential to cause severe damage in cloud systems 5 .…”

“…3 However, this model has met several problems because of the crypto algorithm's extensive data and slow key generation model. 4 This has the potential to cause severe damage in cloud systems. 5 These crypto algorithms are one of the schemes known as public cloud, introduced for the medical cloud environment to secure medical data.…”

“…7 However, security is the primary concern for carrying on medical services through the wireless environment. 8 This key generation concept can avoid Symbols and Abbreviations: DL, Deep learning; ML, Machine learning; IoT, Internet of Things; ABIDE, African buffalo-based International Data Encryption; CS, Cloud server; MRI, Magnetic resonance imaging; ABO, African buffalo optimization; IDE, International data encryption; SA-DS, Secure Authentication based data sharing; MWO, Modified whale optimization; a m n , General symptoms for each disease; n, Cloud database parameter; d p , The particular disease of the affected patient; z (1) 1 , z (2) 2 , z (3) 3 , z (4) 4 , Encryption process; h ′ , Hash function of the public cloud system; h d , Healthcare data card of the patient; r ′ , Randomly selected value; S ′ n , Medical data record; 𝛽 ′ , Actual healthcare information; 𝛼 ′ , Collected healthcare information; a ′ d , c ′ d , Healthcare information from the cloud database; P k+1 , Exploitation performance; e k , User detail; lg 1 F I G U R E 1 Public cryptosystem the third person in the cloud environment by locking the user details. 9 Hence, the closed details are only visible to the medical specialist who can have authenticated access.…”