Digital Signal Processing: How DSP Work? Importance ? Career ?

 Digital Signal Processing (DSP)

Digital signal processing is used to perform a wide variety of signal processing operations. DSP applications include image processing, speech and audio processing, data compression, video coding, audio coding, signal processing for telecommunication, control system, biomedical applications and many more.

The application of digital computation to signal processing have many advantages over analog processing in applications such as error detection and correction in transmission as well as data compression. It is also fundamental to digital technology, such as digital telecommunication and wireless communications. It is applicable to both live streaming data and stored data.

DSP algorithms can be run on general-purpose computers and digital signal processors. DSP algorithms are also implemented on hardware such as application-specific integrated circuit (ASICs). Additional technologies for digital signal processing include more powerful general-purpose microprocessors, graphics processing units, field-programmable gate arrays (FPGAs), digital signal controllers (mostly for industrial applications such as motor control), and stream processors.

How DSP Work?

Digital Signal Processing converts the received signals from the sources (usually in analog form) into digital data that can then be analyzed. Analysis is performed in digital form because once a signal has been reduced to numbers, its components can be isolated and manipulated in more detail than in analog form.

When the DSP work finished, the digital data can be turned back into an analog signal with improved quality. A DSP can filter noise from a signal, amplify frequencies and suppress others.

 

Why DSP is important?

For increased performance, flexibility, configurability, communications, and remote monitoring and control, the power electronics industry is increasingly moving from analog to digital power converters, particularly when high-density power output is required.

Many mission-critical operations in aerospace and defence, as well as some industrial applications, require high output power in the multi-kilowatt range. Given the mission-critical nature of these applications and the extremely rugged conditions in which they must operate, these power converters must also withstand stringent vibration, shock, EMI, humidity, and other environmental settings without breaking down.

Meeting all of these requirements often requires a custom solution from a power converter designer proficient in digital signal processing (DSP) techniques as well as military and aerospace specifications and high-reliability standards.

Here are a few more reasons why DSP is valuable:

·   Power: Real world signals are converted into a domain where abstract scientific and mathematical models are then applied. The result is a powerful processing system.

·  Information: Information can be used to enhance or improve desired aspects of a signal or even to reduce undesirable aspects.

· Adaptation: DSP processes information adaptively. This concept is imperative in a dynamic application such as sound and speech, especially when applied in industrial environments.

· Flexibility: DSP creates flexibility. Changes, updates, customizations, and many other features are available with the implementation of DSP systems.

·   Efficiency: DSP allows users to get the job done efficiently, practically, and cost effectively.

 

Career in Digital Signal Processing (DSP):

Signal processing – the enabling technology for the generation, transformation, extraction and interpretation of information via electronic signals – is essential for our smartphones and wearable devices, as well as the latest health care technologies, digital cameras and our digital assistants like Amazon Echo and Google Home.

Signal Processing Plays a Key Role in Multiple Industries: Unlike in most fields of study, in signal processing, future jobs are not defined by or restricted to a single professional area. Signals are used to transmit information in nearly every imaginable field. They are used extensively in what will likely be a high-growth industry in years to come: health care. Signal processing is essential for the use of X-rays, MRIs and CT scans, allowing medical images to be analyzed and deciphered by complex data processing techniques.

Signal Processing is the Technology of the Future: Many young people are concerned how technology is impacting their future job prospects. But when you’re caught in the tide you swim with it, not against it. That’s why you should explore the possibilities of signal processing, the technology underpinning most of our disruptive innovations.

Signal Processing Can Serve a Social Purpose: Whether addressing inequality, making our economy more sustainable or combatting epidemics, it’s key that researchers and policymakers have access to all the relevant data. Signal processing allows for the expansion of computing power and data storage capabilities, making signal processing engineers indispensable for understanding and tackling our biggest global problems.

 A career in this field isn’t just about employment opportunities or guarding against your job being automated. It’s about contributing to improving the world. Hence, choosing career in digital signal processing is a good and always a smart choice.

Below, are the few names of manufacturers which deal in Digital Signal Processors and Digital Signal Controllers:

NXP Semiconductors

STMicroelectronics

Infineon Technologies

Cirrus Logic

Microchip Technology

NJR Semiconductor

ON Semiconductor

ROHM Semiconductor

Texas Instruments

How you can learn about Digital Signal Processing?

You will start from the basic concepts of discrete-time signals and proceed to learn how to analyze data via the Fourier transform, how to manipulate data via digital filters and how to convert analog signals into digital format. Finally, you will also discover how to implement real-time DSP algorithms on a general-purpose microcontroller. The solid theoretical bases provided are complemented by applied examples in MATLAB 2021 Simulator.

In this next post, you will find some of the DSP Programme performed in MATLAB Simulator which helps you the understand the basic concepts of DSP and how it can be applied to the real-world application fields.

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