找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications; Proceedings of the M Andreas Kling,Fernando J.

[復制鏈接]
樓主: GUST
11#
發(fā)表于 2025-3-23 12:58:25 | 只看該作者
Comparison of EGS4 and Measurements Regarding K-X ray and Bremsstrahlung Photonsdes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts..?.978-3-319-34357-0978-3-319-01342-8
12#
發(fā)表于 2025-3-23 15:08:26 | 只看該作者
13#
發(fā)表于 2025-3-23 21:25:49 | 只看該作者
Monte Carlo Polarimetric Efficiency Simulations for a Single Monolithic CdTe Thick Matrixp-start?your research, this is the book for you...What You‘ll Learn?.Write Python scripts to automate your lab calculations.Search for important motifs in genome sequences.Use object-oriented programming with Python.Study mining interaction network data for patterns.Review dynamic modeling of bioche
14#
發(fā)表于 2025-3-24 01:47:33 | 只看該作者
Low-Energy Electron Scattering in Solids — a Monte Carlo Approachlready program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.?.978-3-030-49722-4978-3-030-49720-0
15#
發(fā)表于 2025-3-24 05:59:05 | 只看該作者
ing methods that help generate samples from complicated generic distributions. The chapter ends with a discussion of important probability inequalities that prove to be useful in later statistics and machine learning chapters.
16#
發(fā)表于 2025-3-24 09:14:06 | 只看該作者
17#
發(fā)表于 2025-3-24 12:08:34 | 只看該作者
18#
發(fā)表于 2025-3-24 14:57:05 | 只看該作者
Monte Carlo Simulation of Few-keV Positrons Penetrating in Solidsw section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient d978-3-030-18547-3978-3-030-18545-9
19#
發(fā)表于 2025-3-24 22:27:03 | 只看該作者
20#
發(fā)表于 2025-3-25 00:13:35 | 只看該作者
 關于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-10 11:22
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
阿克陶县| 三穗县| 嘉祥县| 原平市| 深州市| 佛坪县| 富平县| 浠水县| 图们市| 常熟市| 琼中| 南澳县| 嘉定区| 璧山县| 景泰县| 宁远县| 涟水县| 康乐县| 铜鼓县| 颍上县| 修文县| 射阳县| 星子县| 五家渠市| 阳江市| 眉山市| 娄烦县| 昌乐县| 开封县| 天水市| 阿瓦提县| 诸暨市| 通江县| 科尔| 嘉荫县| 安丘市| 上犹县| 崇义县| 石台县| 潍坊市| 上饶县|