How Many Style Name There Is In People Key Disc Brief Explanation of Digital Signal Processing, Compression, Encryption, and File Translation

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Brief Explanation of Digital Signal Processing, Compression, Encryption, and File Translation

It happens that many people do not know what Digital Signal Processing means, although they hear more and more these words, today. Considering the name, Digital Signal Processing, people are led to think of this process related to digital signals. No; Digital Signal Processing is a method of improving the quality of an analog signal, simply. In fact, the name used (DSP) it is unnecessary, because it affects all types of digital processing. The techniques, and techniques used in DSP only deal with signals that are similar. In digital matters, we can only compress, encrypt, and translate them to another digital format; this (different) process does not require a DSP process. Using the name DSP when referring to digital signals causes confusion.

Let’s take each step one at a time, and use a few examples. Suppose we have an old file and we want to copy its analog signal onto a digital CD, to better protect the data–CDs have a higher reliability to hold the data unchanged, over time. This means that we need to convert the analog signal to digital format, and the best way of doing it is by using DSP techniques, as below. First, we need an analog-to-digital hardware module to convert the analog signal into a format – this is usually a “codec” – then we choose a specific scanning frequency, to do finish this job. Since we are working with audio frequency, 40 KHz scanning frequency should be enough.

Please note this: the scanning frequency must be at least twice the frequency of the original analog signal – the analog audio signals have a frequency in the range of 10 Hz to 16 KHz. After scanning, we have a copy of the analog vinyl record, in a digital file, expressed as a number of numerical digits in binary format.

Unfortunately, our vinyl record is old, and it has a lot of noise; noise is also present on the digital copy, and it must be filtered out, before we burn the digital CD. The next step is to take the digital copy – please remember this: the digital copy still represents the analog signal – and we use it for its mathematical transformation: in this way, we change the data digital paper from the “time-domain” to the “frequency-domain”. This is done gradually, by cutting the digital data into frames of 512, 1024, or 4096 integers in size, and converting them one at a time. When we have information in the frequency-domain, it is easy to filter the noise, and select/amplify only the sound frequency we need. For this we use digital firmware or software filters, which are, in fact, known mathematical algorithms.

When the data is filtered correctly, we need to convert it back to the time-domain, and we do this by using the second transformation. Now we can listen to our data, filtered from (any) noise. If we are satisfied with the quality of the recording, we can burn a CD; otherwise, we can repeat the process above, until the results are exactly what we want them to be. Digital Signal Processing ends here.

Now, we have a CD holding a digital signal – the audio file in this particular case. It may happen that our audio files use too much memory to store, and we can’t pay that much. We want our digital files to use the least amount of memory, so that we can transfer files quickly over the Internet, or we want to store as many files as we can in MP3 small, for example. For this we need the “compression” process, and, implicitly, the “encryption” one.

There are many compression/encryption methods available, and many will be developed in the future. Basically, digital signals are actually numbers – numbers are 2 bytes; a byte is 8 bits; each bit is either a 0 or a 1–and each number includes a single digit in the range 0 to 65535. Now, we see every number in the range 0 to 65535 repeated many times, in all audio files. This information is very important, because it helps us to convert our code into an encrypted code, by using the software compression / encryption “key”. Instead of using, for example, the number 23501 for 1522 times in our digital audio files, we only use the information about that number, meaning we store the value 1522, only once, each such as the number 23501.

The compression/encryption key – this is actually another mathematical function – it is responsible for taking the first digital data and breaking it into numbers of numbers; to replace each number with the number of the time it takes; and preserves the code required to reproduce the original code, which is the original digital data. Usually, the key works with a special memory, called “binary-tree”. In this binary-tree the position of each number represents how many times an integer appears in the entire file (or in a frame), and it also holds the data needed to reconstitute the frame, and then all the audio data.

When the digital audio file is in binary-tree format its size will be reduced – it is compressed – and we can use it for memory storage, or to transfer data quickly. In this binary-tree format this file is also encrypted, plus compressed, and we need the compression/encryption key, in order to reconstitute the original digital signal; otherwise, there is no way we can “decipher” the binary-tree.

Now, what else can we do with our digital audio files? Well, there are many audio file formats, and we may need to convert our audio files from one format to another. The simplest audio files hold data as bits, of 0s and 1s. Other types may contain information in small packages, in series of bytes, integers, or doubles. This last format allows another level of data compressing; However, to convert from one format to another we need appropriate hardware, firmware, or software to read/write drivers. Changing the type of data it is called “translation” or “transformation”, and this is easier to use.

Basically, this is all we do for analog and digital signals. As you can see there is a lot of math involved, but the good news is, all the math and algorithms are standard. A developer doesn’t need to know a lot of math, in order to do his job well. Mathematical algorithms are designed and optimized by teams of engineers and programmers, and we all use them. However, if you intend to create a mastering process, in order to achieve more beautiful results, you should learn to perfect DSP, compression/encryption, and translation. For more information please visit my home page, and try to find other related articles I have written, in various publications on the Internet.

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