Data Compression
Akopọ
Write out the word BANANA in ordinary character codes and it takes 42 bits. Write it out cleverly and it takes 9. Nothing has been thrown away, nothing has been approximated, and the original word can be reconstructed exactly. The saving comes from noticing something the plain encoding ignores: the letter A turns up three times as often as the letter B, and a code that gives A a shorter pattern than B will win.
This lesson covers what data compression is, why it is worth doing, and the two methods this specification examines. You will learn to write data as run length encoding pairs, to build a Huffman tree from a string and read the codes off it, to interpret a tree somebody else has given you, and to calculate exactly how many bits each method saves against plain 7-bit ASCII. You will also learn the situation in which compression makes a file larger, which is a real result and a favourite of examiners.
Awọn Afojusun
- Explain what data compression is.
- Understand why data may be compressed and that there are different ways to compress data. Explain how data can be compressed using Huffman coding. Be able to build a Huffman tree.
- Be able to interpret a Huffman tree.
- Calculate the number of bits required to store a piece of data compressed using Huffman coding.
- Calculate the number of bits required to store a piece of uncompressed data in ASCII.
- Explain how data can be compressed using run length encoding (RLE).
- Represent data in RLE frequency/data pairs.
Àwòrán ọpọlọ
A ti ṣe àwòrán kókó yìí kí o lè rí bí àwọn èrò ṣe so pọ̀.
Ṣí àwòrán ọpọlọ nínú áàpù
Akọ̀wé Ẹ̀kọ́
Àkọsílẹ̀ Ẹ̀kọ́ Pípé wà lórí Ohun Èlò Green Bridge
Gba ohun èlò Green Bridge CBT sórí fóònù tàbí kọ̀mpútà rẹ fún gbogbo ilé ìkàwé IGCSE: ìwé ìdánwò àtijọ́, ìlànà ìdíwọ̀n, àwòrán èrò, káàdì ìkẹ́kọ̀ọ́ àti ẹ̀kọ́ ohùn.
Ìdánwò Ẹ̀kọ́
Oriire fun ipari ẹkọ lori Data Compression. Ni bayi ti o ti ṣawari naa awọn imọran bọtini ati awọn imọran, o to akoko lati fi imọ rẹ si idanwo. Ẹka yii nfunni ni ọpọlọpọ awọn adaṣe awọn ibeere ti a ṣe lati fun oye rẹ lokun ati ṣe iranlọwọ fun ọ lati ṣe iwọn oye ohun elo naa.
Iwọ yoo pade adalu awọn iru ibeere, pẹlu awọn ibeere olumulo pupọ, awọn ibeere idahun kukuru, ati awọn ibeere iwe kikọ. Gbogbo ibeere kọọkan ni a ṣe pẹlu iṣaro lati ṣe ayẹwo awọn ẹya oriṣiriṣi ti imọ rẹ ati awọn ogbon ironu pataki.
Lo ise abala yii gege bi anfaani lati mu oye re lori koko-ọrọ naa lagbara ati lati ṣe idanimọ eyikeyi agbegbe ti o le nilo afikun ikẹkọ. Maṣe jẹ ki awọn italaya eyikeyi ti o ba pade da ọ lójú; dipo, wo wọn gẹgẹ bi awọn anfaani fun idagbasoke ati ilọsiwaju.
- What is data compression? A. Encoding data so it uses fewer bits while representing the same information B. Deleting parts of a file that are not needed C. Converting a file from binary into hexadecimal D. Copying a file to a second storage device Answer: A
- Using run length encoding with frequency first, how is the binary data 00011000 represented? A. 3 0 2 1 3 0 B. 0 3 1 2 0 3 C. 3 2 3 D. 8 0 Answer: A
- Why does run length encoding work poorly on a file of English text? A. Text files are always too large to compress B. Consecutive characters are usually different, so runs are very short C. Text is stored in Unicode rather than in binary D. Run length encoding can only be used on numbers Answer: B
- In a Huffman tree, which characters end up with the shortest codes? A. The ones that occur least often B. The ones that occur most often C. The ones that come first alphabetically D. All characters get codes of equal length Answer: B
- A message of 20 characters is stored in 7-bit ASCII. How many bits does it need uncompressed? A. 27 B. 60 C. 140 D. 160 Answer: C
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Ṣiṣẹ́ lórí àwọn ìbéèrè wọ̀nyí nínú ohun èlò náà
Awọn Iwe Itọsọna Ti a Gba Nimọran
Ṣe Adaṣe Awọn Ibeere Idanwo Adaṣe
Ṣe o fẹ ṣe adaṣe awọn ibeere idanwo adaṣe nipa Data Compression? Ṣe igbasilẹ ohun elo Green Bridge CBT lati wọle si awọn ibeere idanwo adaṣe ati awọn ayẹwo adaṣe kikun fun koko-ọrọ yii.
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