Cooperative relay networks have recently attracted the attention of many researchers as an efficient solution for the multipath fading problem in wireless communications [3]. Using relays in wireless networks aims to provide diversity, widen the coverage area, and reduce the need for high-power transm...
In order to avoid a tremendous increase in model size when using the Gaussian method, more robust sequential approaches were developed, based on the decomposition of the problem into a) determination of the first-stage variables, and b) adjustment of the second-stage variables (Zirngast et al....
[431] employed Neural Response Mixture (NeREM) to learn deep features used in the Mixture of Gaussians (MOG) model [2]. In another study, Chan [475] proposed a deep learning-based scene-awareness approach for change detection in video sequences thus applying the suitable background ...
Additionally, our proposed method has shown robustness to various environmental challenges like Gaussian noise, Gaussian blur, up to 卤30 degrees of rotation, and 20% of occlusion.doi:10.1007/s11042-020-10264-2Kamboj, AmanNational Institute of Technology, Jalandhar, IndiaRani, Rajneesh...
In this work, we develop a novel efficient scan method, combining the Heuris- tically Search (HS) and the Generative Adversarial Network (GAN), where the HS can shift marginal samples to perfect samples, and the GAN can generate a huge amount of recommended samples from noise in a short ...
where, w(t) is a random Gaussian white noise signal with zero mean and unit variance. Apply Scenario Settings Click OK to update the scenario settings and close the dialog box. The app runs the simulation and the input/output response plots update to reflect the new scenario settings. To ...
of the radar environment, but rather to perform some basic testing. The number of targets is limited and target motion is simple. The radar platform doesn’t change position or attitude. Interference is simulated by a simple Gaussian noise generator. The test scenarios are canned; there is no...
In this article, we analyze the expected training error and the\nexpected generalization error in a special case of overrealizable\nscenario, in which output data is a Gaussian noise sequence. Firstly, we\nderived the upper bound of the expected training error of a network,\nwhich is ...
where Re[ ] and Im[ ] denote the real and imaginary part of a complex number, QAM denotes the QAM constellation diagram,N0denotes the power spectral density of an equivalent Gaussian noise process, and map(q) denotes a corresponding mapping rule (Gray mapping is applied here). (bdenotes th...
Specifically, Rayleigh fading and Additive White Gaussian Noise (AWGN) channels along with one-dimensional (line), two-dimensional (circle), and three-dimensional (sphere) mobility conditions are considered. A closed-form expression for the average bit error rate (BER) of CSSM system is derived ...