Source Coding

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The more variable the l i , the more harm the errors in the estimates of the p i can cause in the average of the symbol length. 20
Ex: p 1 = 0.4, p 2 = 0.2, p 3 = 0.2, p 4 = 0.1, p 5 = 0.1 [Approach 1] 0.4 0.2 0 1 0.6 0.2 0 000 0.1 0.1 0 1 0.2 1 0.4 0010 0011 L 1 = 0. 4 × 1+ 0. 2 × 2 + 0. 2 0 1 1 × 3+ 0. 1× 4 + 0. 1× 4 = 1 01 2. 2 bits 21
Page 1 and 2: Source Coding Prof. Ja-Ling Wu Depa
Page 3 and 4: ( i) ( i) message g X , X , , X ( i
Page 5 and 6: 01 { 1110 {{{ 1100 101 00 { 100 { u
Page 7 and 8: Only when = ⇒ = ⇒ − Ni n N H
Page 9 and 10: Theorem : Let a code have codeword
Page 11 and 12: C2 C3 C4 C5 S1 00 0 0 1 S2 01 10 01
Page 13 and 14: i l r S S − + ⇒ i i i i i r S S
Page 15 and 16: − ar ary nnumber mber representa
Page 17 and 18: Noise in Huffman coding Probabiliti
Page 19: the resort to we (2), and (1) , on
Page 23: ) 2 2 3 ( 2 0 ) 2 2 2 ( 2 0 ) 2 2 1

Source Coding

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