Skip to main content

How MATLAB makes the distinction between P-Cores and E-Cores?

  It is known that modern CPUs have both Performance cores (P-cores) and efficiency cores (E-cores), different types of CPU cores that have different purposes and are designed for different tasks. P-cores typically have higher clock speeds and designed for high-performance tasks, while E-cores operate at lower clock speeds and focus on energy-efficient processing. In MATLAB, maxNumCompThreads returns the current maximum number of computational threads. Currently, the maximum number of computational threads is equal to the number of physical cores on your machine. How MATLAB makes the distinction between P-Cores and E-Cores ? NOTE:- Matlabsolutions.com  provide latest  MatLab Homework Help, MatLab Assignment Help  ,  Finance Assignment Help  for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects...

Given that e is defined to be limn→∞(1+1n)n, how do I prove that e=limn→0(1+n)1n?

Matlabsolutions provide latest MatLab Homework Help,MatLab Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.

There are a couple of good ways to go about this, but let’s try to prove the following general statement:
Given some function f, the limit of f(x) as x is equal to the limit of f(1x) as x0+.
Okay, so we start off with the assumption that limxf(x)=L for some L. This means that given any ϵ>0, there exists some number Mϵ such that |f(x)L|<ϵ for all x>Mϵ.
We wish to show that, given any ϵ>0, there exists some number δϵ such that |f(1x)L|<ϵ for all 0<x<δϵ.
This should be pretty easy - simply choose δϵ=1Mϵ. If 0<x<1Mϵ then 1x>Mϵ, and so |f(1x)L|<ϵ by our initial assumption. Because we can do this for all ϵ>0, we have that limxf(x)=Llimx0+f(1x)=L.
From there, simply let f(x)=(1+1x)x for your specific example, and the desired result follows.

Note that the 0+ is crucial here. If we had tried to prove this for the general limit as x0, then we would have had to seek some δϵ which would work for all 0<|x|<ϵ. The problem with this is that 0<|x|<δ does *not* imply that 1x>1δ - it implies that either 1x>1δ or 1x<1δ. Because our initial assumption is related only to the former case, then in general the statement is not true (unless of course we also have that limxf(x)=limxf(x)=L).

Comments

Popular posts from this blog

What are some good alternatives to Simulink?

Matlabsolutions provide latest  MatLab Homework Help, MatLab Assignment Help  for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research. SIMULINK is a visual programing environment specially for time transient simulations and ordinary differential equations. Depending on what you need there are plenty of Free, Libre and Open Source Software (FLOSS) available: Modelica language is the most viable alternative and in my opinion it is also a superior option to MathWorks SIMULINK. There are open source implementations  OpenModelica  and  JModelica . One of the main advantages with Modelica that you can code a multidimensional ordinary differential equation with algebraic discrete non-causal equations. With OpenModelica you may create a non-causal model r...
https://journals.worldnomads.com/scholarships/story/70330/Worldwide/Dat-shares-his-photos-from-Bhutan https://www.blogger.com/comment.g?blogID=441349916452722960&postID=9118208214656837886&page=2&token=1554200958385 https://todaysinspiration.blogspot.com/2016/08/lp-have-look-at-this-this-is-from.html?showComment=1554201056566#c578424769512920148 https://behaviorpsych.blogspot.com/p/goal-bank.html?showComment=1554201200695 https://billlumaye.blogspot.com/2012/10/tagg-romney-drops-by-bill-show.html?showComment=1550657710334#c7928008051819098612 http://blog.phdays.com/2014/07/review-of-waf-bypass-tasks.html?showComment=1554201301305#c6351671948289526101 http://www.readyshelby.org/blog/gifts-of-preparedness/#comment_form http://www.hanabilkova.svet-stranek.cz/nakup/ http://www.23hq.com/shailendrasingh/photo/21681053 http://blogs.stlawu.edu/jbpcultureandmedia/2013/11/18/blog-entry-10-guns-as-free-speech/comment-page-1443/#comment-198345 https://journals.worldnomads.com...

USING MACHINE LEARNING CLASSIFICATION ALGORITHMS FOR DETECTING SPAM AND NON-SPAM EMAILS

    ABSTRACT We know the increasing volume of unwanted volume of emails as spam. As per statistical analysis 40% of all messages are spam which about 15.4 billion email for every day and that cost web clients about $355 million every year. Spammers to use a few dubious techniques to defeat the filtering strategies like utilizing irregular sender addresses or potentially add irregular characters to the start or the finish of the message subject line. A particular calculation is at that point used to take in the order rules from these email messages. Machine learning has been contemplated and there are loads of calculations can be used in email filtering. To classify these mails as spam and non-spam mails implementation of machine learning algorithm  such as KNN, SVM, Bayesian classification  and ANN  to develop better filtering tool.   Contents ABSTRACT 2 1. INTRODUCTION 4 1.1 Objective : 5 2. Literature Review 5 2.1. Existing Machine learning techniqu...