Understanding Shannon's Entropy metric for Information [pdf]
I read your arxiv.org article on Shannon Entropy:
<a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;1405.2061" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;1405.2061</a><p>What I am amazed at is that arxiv accepted this.  I submitted exactly the same argument to them on 27 Jan 2009.  They rejected it.<p>Here it is on my home page:
<a href="http:&#x2F;&#x2F;dsw.users.sonic.net&#x2F;entropy.html" rel="nofollow">http:&#x2F;&#x2F;dsw.users.sonic.net&#x2F;entropy.html</a><p>Entropy is (1) the expected value of (2) the information of an event.<p>You might want to post a link to your answer here and see which of our explanations is more popular:
<a href="https:&#x2F;&#x2F;math.stackexchange.com&#x2F;questions&#x2F;331103&#x2F;intuitive-explanation-of-entropy&#x2F;4270372#4270372" rel="nofollow">https:&#x2F;&#x2F;math.stackexchange.com&#x2F;questions&#x2F;331103&#x2F;intuitive-ex...</a>