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matrenka [14]
2 years ago
15

The section of the cpu that is responsible for performing mathematical operations.

Computers and Technology
1 answer:
nlexa [21]2 years ago
4 0

The CPU executes arithmetic and logic operations in the arithmetic and logic unit (ALU).

<h3>What is an ALU, or an arithmetic and logic unit?</h3>
  • A combinational digital circuit known as an arithmetic logic unit computes arithmetic and bitwise operations on integer binary integers.
  • A floating-point unit, on the other hand, works with floating-point numbers.
  • The component of a central processing unit known as an arithmetic-logic unit performs arithmetic and logic operations on the operands in computer instruction words.
  • An Arithmetic Logic Unit (ALU) is a component found within computers that can execute logical operations in addition to arithmetic operations, such as AND, OR, Ex-OR, invert, etc (e.g. Addition, Subtraction, etc.).

To learn more about arithmetic and logic unit (ALU), refer to:

brainly.com/question/7994884

#SPJ4

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The late seventeenth-century literary period known as the Restoration begins in 1660, the year in which the monarchy (and specifically, King Charles II) was restored to the English throne.
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16. What's the difference between a footnote and endnote?
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I believe it is 'A'

Explanation:

Footnotes appear at the bottom of the relevant page. Endnotes appear in a list at the end of the text, just before the bibliography.

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What are three major events in computer science history?
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Answer: In 1834, Charles Babbage announces the analysis engine.

1943: The birth of Mark I Colossus.

1954: First prototype of desktop calculators.

Explanation:

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ossless compression tools generally use either Huffman coding or Lempel-Ziv-Welch (LZW) coding. Discuss the advantages and disad
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Answer:

It we were asked to develop a new data compression tool, it is recommended to use Huffman coding since it is easy to implement and it is widely used.

Explanation:

The pros and the cons of Huffman coding

Huffman coding is one of the most simple compressing encoding schemes and can be implemented easily and efficiently. It also has the advantage of not being patented like other methods (e.g. arithmetic codingfor example) which however are superior to Huffman coding in terms of resulting code length.

One thing not mentioned so far shall not be kept secret however: to decode our 96 bit of “brief wit” the potential receiver of the bit sequence does need the codes for all letters! In fact he doesn’t even know which letters are encoded at all! Adding this information, which is also called the “Huffman table” might use up more space than the original uncompressed sentence!

However: for longer texts the savings outweigh the added Huffman table length. One can also agree on a Huffman table to use that isn’t optimized for the exact text to be transmitted but is good in general. In the English language for example the letters “e” and “t” occur most often while “q” and “z” make up the least part of an average text and one can agree on one Huffman table to use that on average produces a good (=short) result. Once agreed upon it doesn’t have to be transmitted with every encoded text again.

One last thing to remember is that Huffman coding is not restricted to letters and text: it can be used for just any symbols, numbers or “abstract things” that can be assigned a bit sequence to. As such Huffman coding plays an important role in other compression algorithms like JPG compression for photos and MP3 for audio files.

The pros and the cons of Lempel-Ziv-Welch

The size of files usually increases to a great extent when it includes lots of repetitive data or monochrome images. LZW compression is the best technique for reducing the size of files containing more repetitive data. LZW compression is fast and simple to apply. Since this is a lossless compression technique, none of the contents in the file are lost during or after compression. The decompression algorithm always follows the compression algorithm. LZW algorithm is efficient because it does not need to pass the string table to the decompression code. The table can be recreated as it was during compression, using the input stream as data. This avoids insertion of large string translation table with the compression data.

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