Binary data compression algorithm Binary is a number system widely used in computing technology. Binary data is a number represented by two numbers 0 and 1. Its cardinality is 2, the carry rule is "every two into one", and the borrowing rule is "borrowing one and two", discovered by the 18th century German mathematical philosophy master Leibniz. Current computer systems use essentially binary systems, and data is stored primarily in the form of complements in the computer. The binary in the computer is a very small switch, with "on" to indicate 1, "off" to indicate 0.
The invention and application of computers in the 20th century, known as one of the important symbols of the third technological revolution, because digital computers can only be identified and processed by '0'. The code consisting of the '1' symbol string. Its operation mode is binary. In the 19th century, the Irish logician George Boolean thought of the process of thinking about logical propositions into some algebraic calculus for the symbol "0''. ''1'', binary is the carry system of the binary carry. 0, 1 is the basic operator Because it only uses 0, 1 two-digit symbols, it is very simple and convenient, and easy to implement electronically.
Binary compression - algorithmBinary compression
When programming, there are only two states for each data, and when dfs or bfs has high traversal time complexity, binary compressed data can be used, especially two-dimensional arrays.
1. Binary compression of a two-bit array
E.g:
-+--
----
----
-+--
Normally save the data back to using a two-digit array, '+' -" 1, '-' -" 0, ie
0100
0000
0000
010012345678910
If we use binary compression for an int type of data, it is represented by 16 bits.
There are two ways to express this. In fact, they are all the same. One is from top to bottom and from high to low. One is from top to bottom and from low to high.
From low to high
Int input = 0;
Int[][] data = new int[4][4];
Scanner sc = new Scanner(System.in);
String line = "";
For (int i = 0; i " 4; i++) {
Line = sc.next();
For (int j = 0; j " 4; j++) {
Data[dataIn++] = line.charAt(j);
}
}
For (int i = 0; i " 16; i++) {
If (data[i] == '+') {
Input |= (1 "i);
// System.out.println(Integer.toBinaryString(input));
}
}1234567891011121314151617
From high to low
Int input = 0;
Scanner sc = new Scanner(System.in);
String line = "";
For (int i = 0; i " 4; i++) {
Line = sc.next();
For (int j = 0; j " 4; j++) {
Input = input "1;
Input = line.charAt(i) == '+' ? Input + 1 : input;
}
}
Binary data compression algorithmLZFSE
1, zlib and gzip both encapsulate deflate, more data headers and tails than deflate
1, Apple has open sourced a new lossless compression algorithm LZFSE, which was introduced last year in iOS 9 and OS X 10.10. According to Apple, LZFE's compression gain is the same as ZLib level 5, but it is 2 to 3 times faster and energy efficient.
LZFSE is based on Lempel-Ziv and uses finite state entropy coding, which is based on Jarek Duda.
Entropy coding work done on the asymmetric digital system (ANS). Simply put, ANS is designed to "end the balance of speed and ratio" and can be used for both precision coding and fast coding, as well as data encryption. Use ANS instead of more traditional
There are more and more compression libraries for Huffman and arithmetic coding methods, and LZFSE is listed among them.
Obviously, the goal of LZFSE is not to be the best or fastest algorithm. In fact, Apple pointed out that
LZ4 has a faster compression speed than LZFSE, while LZMA offers a higher compression ratio, but at a price better than Apple
Other options provided by the SDK are an order of magnitude slower. When compression ratio and speed are almost equal, and you want to reduce energy efficiency, LZFSE is Apple's recommended option.
A reference implementation of LZFSE is available on GitHub. Building and running on MacOS is as simple as it is:
$ xcodebuild install DSTROOT=/tmp/lzfse.dst
If you want to build LZFSE for your current iOS device, you can do:
Xcodebuild -configuration "Release" -arch armv7 install DSTROOT=/tmp/lzfse.dst
In addition to the API documentation, Apple also provided a sample project last year showing how to use LZFSE for block and stream compression, which is a practical LZFSE entry resource.
LZFSE was released after Google's brotli, which was open source last year. Compared to LZFSE, brotli seems to be optimized for a different application scenario, such as compressing static web assets and Android APKs. In these cases, compression ratio is the most important.
ZGAR electronic cigarette uses high-tech R&D, food grade disposable pod device and high-quality raw material. All package designs are Original IP. Our designer team is from Hong Kong. We have very high requirements for product quality, flavors taste and packaging design. The E-liquid is imported, materials are food grade, and assembly plant is medical-grade dust-free workshops.
Our products include disposable e-cigarettes, rechargeable e-cigarettes, rechargreable disposable vape pen, and various of flavors of cigarette cartridges. From 600puffs to 5000puffs, ZGAR bar Disposable offer high-tech R&D, E-cigarette improves battery capacity, We offer various of flavors and support customization. And printing designs can be customized. We have our own professional team and competitive quotations for any OEM or ODM works.
We supply OEM rechargeable disposable vape pen,OEM disposable electronic cigarette,ODM disposable vape pen,ODM disposable electronic cigarette,OEM/ODM vape pen e-cigarette,OEM/ODM atomizer device.
ZGAR Disposable Vape 25 Disposable Vape, bar 3000puffs,ZGAR Disposable Vape 25, Disposable E-cigarette, ZGAR Disposable Vape 25 OEM/ODM disposable vape pen atomizer Device E-cig, ZGAR 25 Vape
Zgar International (M) SDN BHD , https://www.sze-cigarette.com