Theme: Expression of signals by time and degree Plan: The Digital Signal Processing



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Independent work

Independent work of Mahmudov Akmaljon

student of KIF 214-19 group

Tashkent University of Information Technologies

named after Muhammad al Khwarazmi

on the subject of systems and signal processing



Theme: Expression of signals by time and degree

Plan:

1.The Digital Signal Processing

2. The Dawn of DSP Processors

Signal_Processor_fundamentals_an_System__4.DSP_core_architecture_.__5._Memory_Architectures__6._Advantages_of_DSP_Processors'>3. Digital Signal Processor fundamentals an System

4.DSP core architecture.

5. Memory Architectures

6. Advantages of DSP Processors

Conclusion

References

The Digital Signal Processing

To understand what is Digital Signal Processing (DSP) let's examine what does each of its words mean. Signal is any physical quantity that carries information. Processing is a series of steps or operations to achieve a particular end. It is easy to see that Signal Processing is used everywhere to extract information from signals or to convert information-carrying signals from one form to another. For example, our brain and ears take input speech signals, and then process and convert them into meaningful words. Finally, the word Digital in Digital Signal Processing means that the process is done by computers, microprocessors, or logic circuits. The DSP has expanded significantly over that last few decades as a result of rapid developments in computer technology and integrated-circuit fabrication. Consequently, DSP has played an increasingly important role in a wide range of disciplines in science and technology. Research and development in DSP are driving advancements in many high-tech areas including telecommunications, multimedia, medical and scientific imaging, and human-computer interaction. To illustrate the digital revolution and the impact of DSP, consider the development of digital cameras. Traditional cameras mainly rely on physical properties of the optical lens, where higher quality requires bigger and larger system, to obtain good images. When digital cameras were first introduced, their quality were inferior compared to cameras. But as microprocessors become more powerful, more sophisticated DSP algorithms have been developed for digital cameras to correct optical defects and improve the signal image quality. As further developments for digital cameras attached to cell phones (cameraphones), where due to small size requirements of the lenses, these cameras rely on DSP power to provide good images. Essentially, digital camera technology uses computational power to overcome physical limitations. We can end the similar trend happens in many other applications of DSP such as digital communications, digital imaging, digital television, and so on. In summary, DSP has foundations on Mathematics, Physics, and Computer Science, and can provide the key enabling technology in numerous applications.




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