Daniel Joseph Antrim

consider again that dot

15 Jan 2021

First Post Testing Hugo


This is a place for dummy text.

Top Level

This is an unattributed quote

This is a quote with an attribution. — Foo Bar 1

Header 2

Hello world

Header 3

Header 4

Some Code Examples

VHDL

library ieee;
use ieee.std_logic_1164.all;
use ieee.numeric_std.all;

entity top is
  port (
    clk : in std_logic;
    rst_n : in std_logic;
    segments : out std_logic_vector(6 downto 0);
    digit_sel : out std_logic
  );
end top;

architecture rtl of top is
begin
  segments <= (others => '0');
end architecture;

C++

This is what I get for C++,

#include <iostream>

int main(int argc, char* argv[]) {
    std::cout << "Hello, world!" << std::endl;
}

Python

And for Python,

import numpy as np

def main() :
    print("Hello, world!")

if __name__ == "__main__" :
    main()

Rust

And everybody’s favorite,

fn main() {
    println!("Hello, world!");
}

Mathematical Formula

The information entropy, \(H\), over a discrete data is given as, \[ H = - \sum_i p_i \cdot log_2 (p_i), \] where the \(p_i\) are the probabilities of codes/states, indexed by \( i \), in the data.

When considering a continuous distribution, interpreted as a probability distribution function that satisfies \( \int_{-\inf}^{+\inf} p(x) dx = 1 \), the information entropy is given by,

\[ H(x) = - \int_{-\inf}^{+\inf} p(x) \cdot log_2[p(x)] dx. \]


  1. Foo Bar is Foo Baz ↩︎