A meaningful and alphabetical approach to measuring information

The development of computer technology in the new information age raises many additional questions, opens up new opportunities and knowledge. But with this, there are many dilemmas that need to be resolved. So, for example, when studying computer hardware, it is important to understand how it processes, remembers and transfers files, what is data coding and in what format information is measured. But the main subject of discussion is the question of what are the main approaches to measuring information. Examples and explanations of each aspect will be described in detail in this article.

Information in Computer Science

To begin to understand information approaches to data storage, it is first necessary to find out what the information sphere represents in the computer sphere and what it shows. After all, if we take computer science as a science, then its main object of study is information. The very word of Latin origin and in translation into our language means "acquaintance", "explanation", "reduction". Each science uses different definitions of this concept. In the computer field, these are all those information about the various phenomena and objects that surround us, which reduce the measure of uncertainty and the degree of our ignorance of them. But, in order to store all files, data, symbols in an electronic computer, it is necessary to know the algorithm for their translation into a binary form and the existing units for measuring the amount of data. An alphabetical approach to measuring information shows how exactly a computer machine converts symbols into a binary code of zeros and ones.

Coding Information by an Electronic Computer

Computer technology is able to recognize, process, store and transmit only information data in binary code. But if it's an audio recording, text, video, graphic image, how can a machine convert different types of data into a binary type? And how are they in this form stored in memory? These questions can be answered if you know the alphabetical approach to determining the amount of information, the content aspect and the technical essence of coding.

The encoding of information is to encrypt the characters in a binary code consisting of the signs "0" and "1". It's technically simple to organize. The signal is, if there is one, zero indicates the opposite. Some are wondering why the computer can not, like the human brain, keep complex numbers, because they are smaller in size. But electronic computing is easier to operate with a huge binary code, rather than storing complicated numbers in your memory.

Computer Calculus Systems

We used to count from 1 to 10, add, subtract, multiply and do various operations on numbers. The computer is only able to operate with two numbers. But does it in fractions of milliseconds. How does the computer machine encode and decode characters? This is a fairly simple algorithm, which can be considered for an example. An alphabetical approach to measuring information, units of measurement of data, we will consider a little later, after the essence of the encoding and decoding of data becomes clear.

There are many computer programs that visually translate the systems of the calculus or text string into binary code and vice versa.

We will carry out the calculations manually. The coding of information is made by the usual division by 2. So, suppose we have a decimal number of 217. We need to convert it into binary code. To do this, divide it by the number 2 until the remainder is zero or one.

• 217/2 = 108 with the remainder 1. Separately, we write out the remains, and they will create our final answer.
• 108/2 = 54. Here the remainder is the number 0, since 108 is completely divided. Do not forget to tag yourself with the leftovers. After all, if you lose at least one number, the original number will be different.
• 54/2 = 27, the remainder is 0.
• 27/2 = 13, write 1 to the remainder. Our numbers from the remainder create a binary code, which must be read in the reverse order.
• 13/2 = 6. Here the unit is in the remainder, we write it out.
• 6/2 = 3 with a remainder of 0. In the final answer, the numbers should be one more than all the actions you performed.
• 3/2 = 1 with the remainder 1. We write down the remainder and the number 1, which is the final division.

If you format the answer, starting with the number in the first action, the result is 10011011, but this is incorrect. The binary number must be rewritten in reverse order. Here is the final result of translating the number: 11011001. A meaningful and alphabetical approach to measuring information uses data of exactly this format for storage and transmission. The binary code is written to the code table and stored there until you need to display it on the monitor screen. Then, the information is translated into the familiar form, called decoding.

The picture clearly shows the algorithm for translating from binary to decimal. It is carried out by a simple formula. The first digit of the code is multiplied by 2 to the power of 0, we add to it the next digit multiplied by 2 to a greater extent, and so on. As a result, as can be seen from the picture, we get the same number as the original one when encoding.

Alphabetical approach to measuring information: essence, units

To measure the amount of data in a text sequence of characters, you need to use the existing approach. It does not matter the content of the text, the main thing is the quantitative correlation of signs. Due to this aspect, the value of the text message encoded on the computer is calculated. In accordance with this approach, the quantitative value of the text is proportional to the number of characters entered from the keyboard. Due to this method of measuring the information volume is often called volumetric. Symbols can be quite different in magnitude. It is clear that such figures as 0 and 1 carry 1 bit of information, and letters, punctuation marks, space - another weight. You can look at the ASCII table to find out the binary code of a particular character. To calculate the required text volume, you need to add the weight of all the signs - the constituent parts of the entire text. This is the alphabetical approach to determining the amount of information.

In computer science, there are many terms that are increasingly used in everyday life. So, the alphabet in computer science means a set of all symbols, including brackets, a space, punctuation marks, Cyrillic symbols, Latin characters, which are nothing else but a textual component. Here there are two definitions, according to which the given value will be calculated.

1. Due to the first definition, it is possible to calculate the occurrence of characters in a text message, when their probability of occurrence is completely different. So, we can say that some letters in Russian words appear very rarely, for example, "ъ" or "ё".

2. But in some cases it is more expedient to calculate the quantity we need by introducing the equiprobable appearance of each symbol. And then another calculation formula will be used.

This is the alphabetical approach to measuring information.

Equal probability occurrence of characters in a text file

To explain this definition, it is necessary to assume that all signs in the text or message appear with the same frequency. To calculate how much memory they occupy in the computer, it is necessary to plunge into the theory of probability and simple logical conclusions.

Let's say the text is displayed on the monitor screen. We are faced with the task of calculating how much computer memory it takes. Let the text consist of 100 characters. It turns out that the probability of the appearance of one letter, symbol or sign will be one hundredth part of the total volume. If you read a book on the theory of probability, you can find such a simple formula that will accurately determine the numerical value of the chance of the appearance of a sign in any position of the text.

Probably, the proof of formulas and theorems will not be interesting to everyone, therefore, taking into account the formulas of well-known scientists, a calculated expression is derived:

I = log ₂ (1 / p) = log ₂ N (bit); 2 ⁱ = N,

Where i is the value that we need to know, p is a numerical value of the possibility of a sign in the text position, N is in most cases equal to 2, because the computer machine encodes the data into a binary code consisting of two quantities.

An alphabetical volumetric approach to measuring information assumes that the weight of one character sign is equal to 1 bit - the minimum unit of measurement. By the formula it is possible to determine what is equal to byte, kilobyte, megabyte, etc.

Different probability of occurrence of symbols in the text

If we assume that the signs appear with different frequencies (respectively, and in any position of the text their probability of occurrence is different), then we can say that their information weight is also different. It is necessary to calculate the measurement of information according to another formula. The alphabetical approach of topics is universal, which implies both an equal and different possibility of the frequency of occurrence of a sign in the text. We will not touch upon the complex formula for calculating this quantity, taking into account the different probability of occurrence of the symbol. It is necessary to understand that such letters as "ъ", "х", "ф", "ч", in Russian words are encountered much less often. Therefore, it becomes necessary to consider the frequency of appearance according to another formula. After making some calculations, the scientists came to the conclusion that the information weight of the rarely encountered symbols is much greater than the weight of the letters that are often encountered. To calculate the amount of text, you need to take into account the amount of repetitions of each character and its information weight, as well as the size of the alphabet.

Measurement of information: the subtleties of the content aspect

You can ignore the alphabetical approach to measuring information. Informatics offers one more aspect of measuring data - meaningful. Here, a slightly different problem is being solved. Suppose a person sitting at a computer receives information about a phenomenon or some object. It is clear beforehand that he does not know anything, so there is a certain number of possible or expected options. After reading the message, the uncertainty disappears, leaving one option, the value of which must be calculated. We turn to the auxiliary formula. The value will be calculated in the minimum unit - bits. Like the alphabetical approach to measuring the amount of information, the correct formula will be chosen taking into account 2 possible situations: different and equal probability of occurrence of events.

Events encountered with equal probability

As in the case when an objective alphabetic approach to the measurement of information is applied, the required formula in the meaningful approach is calculated taking into account the already known regularity that the scientist Hartley has deduced:

2 ⁱ = N,

Where i is the magnitude of the event that we need to find, and N is the number of events encountered at equiprobable frequency. The value of i is considered in the minimum unit of calculation - bits. One can express i through the logarithm.

Example of calculation of equiprobability event

Let's say that we have 64 pelmis on a plate, in one of which a surprise is hidden instead of meat. It is necessary to calculate how much information the event contains when it was this pelmen that was pulled out with a surprise, that is, to measure the information. The alphabetic approach is as simple as the objective one. In two cases, the same formula would be used to calculate the quantity of information materials. We substitute the well-known formula for the quantity: 2 ⁱ = 64 = 2 ⁶ . Result: i = 6 bits.

Measurement of information taking into account the different probability of occurrence of an event

Suppose we have an event with the probability of occurrence of p. We will assume that the value i, calculated in bits, is a number characterizing the fact that the event occurred. Based on this, it can be argued that the values can be calculated from the existing formula: 2 ⁱ = 1 / p.

Differences between the alphabetic and informative approaches to the information dimension

Than the volume approach differs from the substantial? After all, the formulas for calculating the quantities of information are completely the same. The difference is that the alphabetic aspect can be used if you work with texts, while the content one allows you to solve any problems of probability theory, calculate the amount of information of some event taking into account its probable appearance.

conclusions

An alphabetical approach to measuring information in the same way as a meaningful one, gives an opportunity to find out which units of data and what volume will be occupied by text signs or any other information. We can translate any text and numeric files, messages into computer code and back, while always knowing how much memory they will occupy in a computer.