Capture Instance 和 Occurrence
標簽： Occurrence Instance Capture
上傳時間： 2013-06-28
上傳用戶：fnggknj
This is GPS Matlab findPreambles finds the first preamble Occurrence in the bit stream of each channel. The preamble is verified by check of the spacing between preambles [6sec] and parity checking of the first two words in a subframe. At the same time function returns list of channels, that are in tracking state and with valid preambles in the nav data stream.
標簽： findPreambles Occurrence the preamble
上傳時間： 2013-12-23
上傳用戶：秦莞爾w
We address the problem of predicting a word from previous words in a sample of text. In particular, we discuss n-gram models based on classes of words. We also discuss several statistical algorithms for assigning words to classes based on the frequency of their co-Occurrence with other words. We find that we are able to extract classes that have the flavor of either syntactically based groupings or semantically based groupings, depending on the nature of the underlying statistics.
標簽： predicting particular previous address
上傳時間： 2016-12-26
上傳用戶：xfbs821
Compression using lempel-ziv -for a dictionary size of 2k -provide dictionary Lempel ziv algorithm is a dictionary based algorithm that addresses byte sequences from former contents instead of the original data. This algorithm consists of a rule for parsing strings of symbols from a finite alphabet into substrings, whose lengths do not exceed a prescribed integer and a coding scheme which maps these substrings sequentially into uniquely decipherable code words of fixed length. The strings are selected so that they have nearly equal probability of Occurrence. Frequently-occurring symbols are grouped into longer strings while occasional symbols appear in short strings.
標簽： dictionary Compression lempel-ziv provide
上傳時間： 2014-01-07
上傳用戶：我們的船長
) Compression using huffman code -with a number of bits k per code word -provide huffman table Huffman coding is optimal for a symbol-by-symbol coding with a known input probability distribution.This technique uses a variable-length code table for encoding a source symbol. The table is derived in a particular way based on the estimated probability of Occurrence for each possible value of the source symbol .Huffman coding uses a specific method for representing each symbol, resulting in a prefix code that expresses the most common characters using shorter strings of bits than those used for less common source symbols.The Huffman coding is a procedure to generate a binary code tree.
標簽： code Compression huffman provide
上傳時間： 2017-05-30
上傳用戶：yuchunhai1990
atlab code for Non-negative Factorization of the Occurrence Tensor from Financial Contracts https://arxiv.org/pdf/1612.03350.pdf,
標簽： tensor_n
上傳時間： 2020-01-01
上傳用戶：dawn1818
atlab code for Non-negative Factorization of the Occurrence Tensor from Financial Contracts https://arxiv.org/pdf/1612.03350.pdf, which
標簽： tensor
上傳時間： 2020-01-01
上傳用戶：dawn1818
