Probability density

In this study, we suggested an FSO system with RIS assistance to mitigate the effects of signal blockage in the communication system, atmospheric turbulence, and UAV’s misalignment-induced fading. In a free-space environment with obstacles, the probability density function and cumulative distribution functions of an FSO system made up of RIS are derived.

8p vithomson 02-07-2024 0 0   Download

In this paper, the authors present a method to solve these problems. Wherein, the motion of targets is represented in the mixed coordinate system 3D base on combining PHD (Probability Hypothesis Density) and JPDA (Joint Probability Data Association). This method can track multiple targets in the most general case, that is to change the target number, system model and measurement model which is non-linear as the noise is non-Gaussian.

9p viambani 18-06-2024 3 1   Download

International conference GIS-Ideas 2023: Geospatial integrated technologies for natural hazards and environmental problems is a collection of articles about: Determination of the optimal density contrast in the seafloor depth inversion from gravity anomalies using the Gravity-Geologic method on the central East Sea; Impact of urbanization on seawater quality in Quang Ninh province; Forecast of submarine landslides related to the reactive probability of the fault system in the Southeast Vietnam continental shelf and adjacent areas; Applying machine learning algorithms to classify forest cove...

442p tukhauquantuong1011 22-04-2024 4 2   Download

Part 1 book "Geometry of quantum states - An introduction to quantum entanglement" includes content: Convexity, colours and statistics; geometry of probability distributions; much ado about spheres; complex projective spaces; outline of quantum mechanics; coherent states and group actions; the stellar representation; the space of density matrices.

245p muasambanhan07 18-02-2024 4 1   Download

Probability is the bedrock of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in probability that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of probability to machine learning, Bayesian probability, entropy, density estimation, maximum likelihood, and much more.

319p viironman 02-06-2023 9 5   Download

Accurate genotype imputation can greatly reduce costs and increase benefits by combining whole-genome sequence data of varying read depth and array genotypes of varying densities. For large populations, an efficient strategy chooses the two haplotypes most likely to form each genotype and updates posterior allele probabilities from prior probabilities within those two haplotypes as each individual’s sequence is processed.

12p vinarcissa 21-03-2023 6 1   Download

Part 1 of ebook "Mathematical statistics for economics and business" provide readers with content about: elements of probability theory; random variables, densities, and cumulative distribution functions; expectations and moments of random variables; parametric families of density functions; basic asymptotics; sampling, sample moments and sampling distributions;...

388p damtuyetha 16-02-2023 5 3   Download

In this paper, the characteristics of wind speed at 20 m height at the Bac Lieu atmospheric physic station (Bac Lieu station) in 2016 were evaluated using the Weibull distribution function.

7p vipagani 24-10-2022 8 3   Download

Part 1 of book "Introduction to machine learning" provide with knowledge about: a taste of machine learning; probability theory; basic algorithms; density estimation; limit theorems; panzer windows; exponential families; maximum likelihood estimation;...

98p britaikridanik 05-07-2022 26 4   Download

Lecture Probability Theory - Lecture 4: Binomial Random Variable Applications, Conditional Probability Density Function and Stirling’s Formula includes the following topics: The Normal Approximation, The Poisson Approximation, Conditional Probability Density Function, Stirling’s Formula.

34p cucngoainhan0 10-05-2022 18 1   Download

In this chapter, we will focus on two random variables, but once you understand the theory for two random variables, the extension to n random variables is straightforward. We will first discuss joint distributions of discrete random variables and then extend the results to continuous random variables.

15p cucngoainhan0 10-05-2022 13 1   Download

Lecture Probability Theory - Lecture 8: One Function of Two Random Variables. Classic problem of finding the probability density function of the sum of two random variables in terms of their joint density function. Find the density function of the sum random variable Z in terms of the joint density function of its two components X and Y that may be independent or dependent of each other.

33p cucngoainhan0 10-05-2022 10 1   Download

Lecture Probability Theory - Lecture 9: Two Functions of Two Random Variables. How to find the joint probability density function of two functions of two random variables X and Y, from the joint probability density function of X and Y is discussed here. In particular, when X and Y are independent and jointly Gaussian random variables, their magnitude and phase functions are shown to be independent, whereas the independence of the magnitude and phase functions is no longer true when X and Y are correlated Gaussian random variables. As usual, all relevant density functions are derived here.

26p cucngoainhan0 10-05-2022 9 1   Download

Lecture Probability Theory - Lecture 11: Conditional Density Functions and Conditional Expected Values. In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value – the value it would take “on average” over an arbitrarily large number of occurrences – given that a certain set of "conditions" is known to occur. If the random variable can take on only a finite number of values, the “conditions” are that the variable can only take on a subset of those values.

18p cucngoainhan0 10-05-2022 4 1   Download

Aklavinone has an anthraquinone-based chromophore and its backbone highly resembles the kernel of some anthracycline antibiotics that possess anticancer activity, e.g., daunomycin. Since aklavinone’s structure possesses many –OH groups and 2 keto groups, it is quite probable that certain tautomeric equilibria may occur. Presently, aklavinone prototropic tautomers possessing embedded anthraquinone moiety have been investigated quantum chemically by using density functional theory at the levels of RB3LYP/6-31G(d) and RB3LYP/6-31G(d,p).

11p langthannam 29-12-2021 15 0   Download

Lecture Introduction to Stochastic Processes: Lesson 6 provide students with knowledge about a small digression; third step: the verification; extensions that finish the proof of theorem; properties of homogeneous poisson processes; probability density function;...

15p bachnhuocdong 23-12-2021 9 0   Download

Lecture ELEC3540 analog and digital communications: Chapter 4 - Probability and random analysis. After completing this section, you will understand the knowledge about Definitions used in statistics; Basic statistical variables; probability density functions.

34p lazzaro 03-12-2021 16 4   Download

Tumor stroma interaction is known to take a crucial role in cancer growth and progression. In the present study, it was performed gene expression analysis of stroma samples with ovarian and breast cancer through an integrative analysis framework to identify common critical biomolecules at multiomics levels. Gene expression datasets were statistically analyzed to identify common differentially expressed genes (DEGs) by comparing tumor stroma and normal stroma samples.

11p thiencuuchu 27-11-2021 9 1   Download

PLINK is probably the most used program for analyzing SNP genotypes and runs of homozygosity (ROH), both in human and in animal populations. The last decade, ROH analyses have become the state-of-the-art method for inbreeding assessment.

14p vijeeni2711 24-07-2021 13 0   Download

In the duty-cycled networks, packet delay is greatly affected by node deployment, therefore we aim to determine node density in a wireless sensor network in order to guarantee the average E2E delay given network parameters using the probability theory. Simulation results show that the proposed node deployment method consumes less energy while requiring a smaller number of sensor nodes than those of other existing works.

13p cothumenhmong11 05-05-2021 19 1   Download