IEEE

A New Approximation for Average Symbol Error Probability over Log-Normal Channels

Abstract: The average symbol error probability(ASEP) is an important measure to evaluate the performance of different modulation techniques over fading channels. The ...
IEEE

Effectiveness of Normal Probability Density Function in Modelling Safety Score Distribution

Abstract: The normal distribution model has strong application in mathematical and statistical research. In communication system, each electron component has a safety score, aiming to measure the its ...
GitHub

Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

The proposed method estimates the per-pixel surface normal probability distribution, from which the expected angular error can be inferred to quantify the aleatoric ...
Visual Studio Magazine

Wasserstein Distance Using C# and Python

The Data Science Lab Wasserstein Distance Using C# and Python Dr. James McCaffrey of Microsoft Research shows how to compute the Wasserstein distance and explains why it is often preferable to ...
GitHub

AttributeError: module 'tensorflow_probability.python.bijectors' has no attribute 'Shift'

2020-12-28 18:32:50.699423: I tensorflow/core/platform/cpu_feature_guard.cc:145] This TensorFlow binary is optimized with Intel(R) MKL-DNN to use the following CPU ...
Scientific Research Publishing

An Algorithm for Generating Random Numbers with Normal Distribution ()

A new algorithm is suggested based on the central limit theorem for generating pseudo-random numbers with a specified normal or Gaussian probability density function. The suggested algorithm is very ...