Final answer:
Huffman coding uses a static frequency table for encoding, efficient for known data sets but not for changing patterns, while Adaptive Huffman coding updates the frequency table dynamically, making it suitable for data streams but increasing complexity and potential overhead.
Step-by-step explanation:
Differences Between Huffman Coding and Adaptive Huffman Coding
The main differences between Huffman coding and Adaptive Huffman coding relate to their approaches to encoding information based on the frequency of data appearances.
Huffman Coding
Huffman coding involves generating a static frequency table before the encoding process begins. The table is created by analyzing the entire set of data to determine the frequency of each data item. Codes are then assigned to data items in such a way that more frequent items have shorter codes, which leads to data compression. A major advantage of Huffman coding is its efficiency in compressing data without losing any information. However, it's not well-suited for data streams where the frequency of items can change since the frequency table remains static.
Adaptive Huffman Coding
Conversely, Adaptive Huffman coding updates the frequency table dynamically as data is being processed. This method adjusts to data on the fly, making it more suitable for streaming data where the frequencies of data items can change over time. The adaptability provides a clear advantage in terms of flexibility. However, this method can be more complex and may require additional overhead to handle the frequent updates, potentially making it slower than traditional Huffman coding.
Advantages and Drawbacks
Huffman Coding Advantages: efficient for known data sets, no need for frequency table transmission.
Adaptive Huffman Coding Advantages: flexible, handles changing data patterns well.
Huffman Coding Drawbacks: not suitable for data with unknown or changing patterns.
Adaptive Huffman Coding Drawbacks: more complex, potentially slower due to updates.