Hi, welcome to the model four of discourse, that is software for software defined radio in the previous
module, we have discussed about the communication layer and we have seen there are different layers
in the communications system, whether it can be our Samodurov TCAP model.
So in this first topic, we are going to learn about the processing architecture for next year.
Since due to the advancement in the field of microelectronics and microprocessor system, we have seen
a huge advancement in the software defined.
You do feel.
Moreover, several types of processors can be used, used to depend on need which we will going to cover.
For example, there are different kinds of protests outside of labor, but the selection criteria is
very important for that application.
Therefore, we are going to discuss different type of processes.
So first one is that general-purpose processor.
So it provides a high level of flexibility in terms of the configurability.
It also provides ease in implementing a new design.
They are power inefficient and not useful for mathematical operations.
So if you want to perform a mathematical calculation, they are not very useful.
The next one is a digital signal processing.
This is also known as the DSP.
So it is used for performing mathematical computation and it can be also used for the new module implementation
of these telecommunication.
Suppose, for example, we have developed a module in a communication system.
We can use the DSP to implement this very much efficiently.
It is relatively power efficient.
For example, they are used in the cellular phones.
Moreover, it is not suitable for high computation process requirements.
So for the case of medium process computation requirement, this is useful.
The next one is the full programmable gate areas.
They're also called PGD.
So the equities are efficient for some DSP because it can implement multiple operations at a given time
if you can implement the particular operations in that p.g.
So it might be more efficient when compared to DSP.
The next one is the graphics processing unit that is GPU and we have seen a lot in terms of context
of image processing or machine learning so that GPS are computationally very powerful and they provide
optimized and extradicted libraries for images, video algebra and signal processing.
So nowadays a lot of optimized video of signal processing or jibla evaluation, video processing sort
of level, which we can directly use in our program to optimise the process and make it faster and are
easily learn the machine learning algorithm on Asgeir.
So nowadays there are some estimates are coming in which in the basement section there are views which
are which can be used for the machine learning applications.
The next one is the advance disk machines that is also known as Army.
So the army is based on the risk that is reduced instruction, set computing.
So the full form of the risk is reduced.
Instruction.
Reduced instruction.
Said.
Computing.
So it is a low cost, small size and less power consumption with good computational capabilities, and
it has a small form factor which make it suitable for mobile communication and computing.
So nowadays you can see in your smartphone, there are some other processors have used the next advantages.
New family of nine processors, which can actually signal processing algorithms and function to speed
up applications such as machine learning or deep learning.
Computer vision has been also introduced in the high risk systems.
So in this topic we have learned about the processing architecture of Hadayet.
There are different architectures like a GPU, CPU or DSP or the machines.
So we have started about them.
And next we are going to learn as their software.