In This Article
What is Digital Signal Processor (DSP)?
Digital Signal Processor or DSP refers to a special type of microprocessor designed to execute complicated mathematical calculations required to process digital signals in particular.
In technical terms, the architecture of a DSP typically contains a ROM or Read Only Memory, which is integrated into the chipset.
These chips are usually made on MOS or Metal Oxide Semiconductor Integrated Circuit chips or ICs and have a wide range of applications in the real world.
- A Digital Signal Processor deals with the subfield of signal processing by manipulating information signals mathematically in order to improve or modify them.
- A DSP can process data in real time and therefore is very quick, making it ideal for using in devices that need minimum or no delays.
- DSP uses digitized audio, video, voice, position, and temperature signals to convert them into another signal and display them.
- These special processors are much better in performance than most of the general-purpose microprocessors when it comes to processing digital signal algorithms successfully, being able to do it incessantly in real-time.
Understanding Digital Signal Processor (DSP)
A Digital Signal Processor, just as the name implies, deals with processing digital signals.
Ideally, different converters such as the ADC or Analog to Digital Converter receive the real-world signals and convert them into digital format of 0s and 1s.
It is the DSP that takes it over from here. It captures the digitized data and information and starts processing it and eventually feeding it back to the real world for use.
This process is done by these special processors in either of the following two ways:
- In an analog format by sending them through a DAC or Digital to Analog converter or
Whichever way is followed, everything happens very quickly in the DSP and the computer uses this information for different operations and controls such as:
- Home theater systems
- Telephony and lots more.
Ideally, the signals are compressed to send them more efficiently and quickly from one location to another as well as to improve the quality of the signals by manipulating the data and information that are usually not sensed by humans.
These signals include:
- Computer enhanced medical images
- Echo cancellation in mobile phones and more.
The DSPs are typically represented as discrete units such as:
- Discrete domain signals
- Discrete frequency and
- Discrete time.
The features of these signal processors also include different other subfields such as:
- Communication signal processing
- Digital image processing
- Radar signal processing and
- Sensor array processing.
In the architecture of a DSP, you will find the following main components:
- A DSP chip – This is the brain of the processor and is responsible for performing all the essential calculations and algorithms.
- A memory – This is where all the algorithms of the digital processor are stored.
- A program memory – This is used to store the programs that it needs to use for processing.
- A data memory – This is used to store the data and information about the programs that it needs to process.
- A compute engine – This actually helps in performing different mathematical calculations, accessing and processing the program stored in the program memory and the data stored in the data memory.
- Input/Output – This helps in connecting to the outside world by performing a wide range of varied functions.
The functionality of these dedicated Integrated Circuits may also be produced by using FPGA or Field Programmable Gate Array chips.
Yes, the real-world signals can be processed and enhanced in their analog form itself, but doing it digitally offers significant benefits such as accuracy and high speed. This is actually facilitated by the specially designed Digital Signal Processors.
What Does a DSP Do?
A Digital Signal Processor handles digital signals and converts them to another type of signal by processing the different programs, data and information mathematically.
Ideally, the working process of the DSP is as follows:
- Taking in different digitized signals of the real world such as audio, video, voice, temperature and others
- Performing some mathematical calculations on the data and other signals and
- Converting them into another signal and
- Displaying them as the final output.
In order to convert or update the digitized signals, different types of mathematical calculations are performed by the Digital Signal Processor which includes:
- Multiplication and
All these calculations are performed very quickly with the ultimate goal of filtering, measuring and compressing a continual stream of analog signals from the real world.
These processors come with unique memory architectures, as mentioned above, which helps them to fetch multiple instructions and data at the same time.
Being dedicated, these special processors have much enhanced power efficiency than the general purpose microprocessors.
This makes them suitable for use in smaller devices that usually have power constraints.
What are the Types of DSP?
Ideally, there are two basic types of DSPs namely, Fixed-point Digital Signal Processors and Floating-point Digital Signal Processors.
Fixed Point DSP:
Here, each number can be specified by at least 16 bits and in different patterns. Also, the fractional point position is fixed and identical for the operands and the operation result. These are used in flexible embedded applications due to their low power and cost.
In fixed point systems, the speed of operation is usually expressed in MIPS or Million Integer Operations Per Second.
Floating Point DSP:
Here, 32 bits at least are used to store every value and the numbers signified are not spaced evenly. However, the programs are simple but they consume more power and are expensive.
In the floating point systems, however, the speed of operation is denoted in MFLOPS or Million Floating Point Operations Per Second.
Most of the DSPs produced today use fixed-point arithmetic due to their relatively lesser hardware complexity, which offers both speed and cost benefits.
Moreover, in the real world signal processing scenario the extra signal range offered by floating point is not required.
However, the floating point DSPs are quite valuable in situations where you need a more dynamic range.
The more expensive and complex hardware of these signal processors also reduces the complexity and cost of software development.
And, most importantly, these DSPs make it much easier to use algorithms in floating point.
Digital Signal Processor Examples
Different companies produce different Digital Signal Processors with different features such as Texas Instruments produces the C6000 series processors with separate data and instruction caches and 1.2 GHz clock speed and 64 EDMA channels.
Freescale produces the MSC81xx, a multi-core DSP with four programmable cores, each with a clock speed of 1 GHz.
Some other examples of DSPs include:
- The multi-core and multi-threaded XMOS processors with a speed ranging between 400 MIPS and 1600 MIPS
- CEVA Inc produces three separate families of DSPs with single or dual MACs and 16 bit or 32 bit word widths
- SHARC-based DSPs that operate at 66 MHz and 198 MFLOPS or 400 MHz and 2400 MFLOPS
- NXP Semiconductors produces processors that are optimized with TriMedia VLIW technology for audio and video processing
- CSR produces processors of the Quatro family of SoCs that can be used for scanners and copiers for their document image data processing abilities and
- DSPs produced by Microchip Technology are PIC24 based and operate at a rate of up to 40 MIPS.
Apart from these, even the general purpose, embedded RISC processors can also function like a DSP. For instance, the OMAP3 processors come with an ARM Cortex-A8 and a C6000 DSP.
Moreover, there is a new generation of DSPs used especially in the field of communications that combine both hardware acceleration and digital signal processing functions. Some of these processors that have already made it to the mainstream include the CEVA XC4000 and ASOCS ModemX.
And, the Huarui-2 and Huarui-3 from The Nanjing Research Institute of Electronics Technology of China Electronics Technology Group is designed to function at a speed of 0.4 TFLOPS to offer a much better performance as compared to other mainstream digital signal processing chips.
Is DSP a Microprocessor or Microcontroller?
Ideally, a DSP processor is a microprocessor that comes with a special architecture and helps in processing digital signals at a quick speed according to the operational needs.
Microcontrollers are more like small computers that have program memory and operate on a single Integrated Circuit.
There are several differences in the design and architecture of the DSP processor and microcontrollers.
For example, the DSP processors do not have the following as microcontrollers:
- A flash program memory and therefore needs software to function
- A non-power, erasable program memory and
- An EPROM store capability.
However, these signal processors can execute integer mathematical operations much faster than the microcontrollers, especially while managing floating point operations due to their specialized architecture.
These processors are not designed to function like multi-feature devices having different ways to interface with the outside world.
Instead, they are typically designed to function as I/O devices having swift calculating machinery.
The microcontrollers can typically function as multi-feature devices and on test boards, not requiring an appropriately designed board to operate flawlessly.
What are DSP Algorithms?
The Digital Signal Processing Algorithms are detailed, step-by-step modus operandi of the mathematical calculations performed by the DSPs to work on digital signals.
These algorithms usually run on a wide range of diverse platforms such as:
- Regular computers
- Microprocessors used for general purpose
- Hardware built for specific purposes such as the ASICs or Application Specific Integrated Circuits
- Digital controllers
- Different graphics processing applications that include an image or a video and
- Traditional stream processing.
These sets of rules make the complex digital signal processing relatively simpler and offer several benefits which include but are not limited to error detection, transmission correction, and data compression.
Where are Digital Signal Processors Used?
The Digital Signal Processors are typically used where there is a need to convert typical analog signals for use in an operation and make them usable.
It is the design and features of these processors that allow them to be used in a wide range of applications, fields, and devices.
DSP are extensively used in different and common consumer electronic devices such as:
- Mobile phones
- High Definition Televisions or HDTVs and
- Disk drives.
Apart from that, Digital Signal Processors are also used widely in several different fields which include but are not limited to:
- Audio signal processing
- Speech recognition and processing systems
- A few financial and statistical signals
- Spectral density estimation
- Audio and video coding
- Image compression and
- Different control systems.
It is because it is programmable that you see a DSP being used in such a wide variety of applications.
Why is DSP Faster?
The Digital Signal Processors are relatively faster as compared to the general purpose processors because they are specially designed to offer optimized performance in two specific areas.
One is to expedite the common mathematical operations in the hardware, and two is to better handle the real-time data streams due to their specific memory architecture design.
Another significant reason for the DSPs being faster and more efficient in processing different signals and data types is their programmability.
This allows the users to make amendments to a few specific parameters of the system easily and when required so that they can accommodate the application very quickly and easily.
In short, the Digital Signal Processors are meant for digital signal exploits and for handling larger instruction sequences ultra-fast and more efficiently, which includes multiply and add, shift and add, and more.
Is a DSP Necessary?
Yes, you will need a Digital Signal Processor as that will provide you with a lot of benefits. One of the most significant benefits is that it will improve the quality of the signals.
In simple words, a DSP is necessary to improve the value of hearing protection overall by not exposing the users to unhealthy noise without compromising the speech signal or communication.
Just as it is needed in an audio system to hear clear sound from the speakers, it is also needed in computer vision and a computational camera that incorporates audio.
A DSP is also necessary to ensure that mobile machine learning consumes less power and performs better.
The exceptional data manipulation abilities of the DSPs and the specific algorithms based on linear system theory and the mathematics of communications allow them to perform intricate operations to reduce or enhance explicit traits of a signal.
These convolution algorithms allow them to implement filtering to manipulate an input signal so that only the desired frequencies are produced as output.
A DSP is also necessary to figure out a particular pattern of intensities and frequencies in a signal. This helps the speech recognition engines detect particular sequences of phonemes and sounds.
These processors are most ideal for use in battery powered products because they consume much less power due to the smaller number of transistors in them.
It is also useful for other cost-effective applications because these are inexpensive to produce due to their simplicity.
Sometimes, DSPs are also necessary for multiprocessing, especially those that come with additional data buses, on-chip memory and several arithmetic execution units.
These particular processors are typically used in video conferencing equipment since they can compress video signals in real time for transferring over the internet and decompress and reconstitute them at the receiving end.
What Programming Language is Used for a DSP?
Theoretically, Digital Signal Processing can be done by using any programming language as with other engineering and science tasks such as BASIC, C and assembly language.
Typically, people are also known to use the following languages:
- Python and
However, in most cases, C++ is the preferred language among computer scientists as well as other professional programmers. And, there are several good reasons behind it such as:
- It being involved closely with the hardware allows coding close to the hardware
- It uses dynamic memory management which allows large scale applications using lower memory and power
- It allows converting floating points to fixed point which is essential for the DSP language ensuring fewer errors and less time consumption
- It allows object-oriented programming that reduces redundancies and helps in producing applications with fewer codes and
- Since it is compiled and not interpreted, it allows the programs to run faster and improve the performance.
Typically, it is the versatility and power of C that give it a significant edge over the other programming languages for digital signal processing.
What are DSP Cores?
The typical definition of a DSP core is a processor that is meant to be used as a building block while creating a chip. These are not packages as it is with the off-the-shelf chips.
However, different vendors may define DSP cores in a different way. For example:
- Texas Instruments includes the processor as well as the peripherals and memory in the definition
- Clarkspur Design and DSP Group do not include peripherals but include memory in their definition of DSP cores and
- SGS-Thompson excludes both peripherals and memory from their definition of DSP cores.
Whatever it is, several modern DSP designs do not come with any memory as the original LSI DSP core circa 1999 and the earlier TI DSP core circa 1996 did.
There may be two particular reasons behind this, such as:
- The manufacturer may want to use multiple cores on the chip to communicate through shared memory or
- To add virtual memory support.
Therefore, the memory hierarchy is designed separately.
However, the DSP core-based method allows the system designers to incorporate several other things on a single Integrated Circuit such as:
- A programmable DSP
- Interface logic and other custom elements.
What is the Signal in DSP?
The signal in a DSP is digital. It is actually a discrete time which is a calculated amplitude signal. This signal typically contains the values from a countable and discrete set and can be mapped to a subset of numbers one-to-one.
In most cases, these sets are finite and can be represented in a fixed width or fixed-point words that are either companded or proportional to the values of the waveform. It may also be represented in floating-point words.
These digital signals are typically produced during the conversion process of analog signals to digital formats.
This conversion process may occur in two specific steps such as:
- Sampling – This generates a discrete time signal of continuous value and
- Quantization – This swaps each sample value with an estimate selected from the specific discrete set.
Usually, the digital signals are characterized differently by means of pulse code modulation such as:
- 8 bits or 256 levels
- 16 bits or 65,536 levels
- 24 bits or 16.8 million levels and
- 32 bits or 4.3 billion levels.
Here the amount of quantization levels is not essentially restricted to powers of two.
Do Computers Have a DSP?
Yes, computers also have Digital Signal Processor but just as every modern computer system is powered by a microprocessor that does not mean all of them are also equipped with a DSP.
You may mix a CPU with a DSP since the former also deals with digital data, but that is not true.
The DSPs are specially designed to manipulate digital signals by performing some mathematical calculations on their own pretty quickly.
It is all due to their high-speed bit-manipulation and arithmetic hardware which allows a myopic focus on mathematics.
- Powerful processing – In the real world, the signals are first changed into a particular domain where theoretical mathematical and scientific models are applied. DSP helps in creating a much better and more powerful processing system.
- Information – These processors help in enhancing or reducing the desired and undesired aspects of the signal as the case may be.
- Adaptation – These signal processors can process data and information adaptively which is essential in the case of any dynamic applications.
- Flexibility – The DSP systems offer greater flexibility to make changes, update, and customize for specific implementations.
- Efficiency – A DSP will allow you to get your job done much more practically, efficiently, and cost-effectively.
Some other advantages of using a DSP is as follows:
- High accuracy
- Comparatively cheaper
- Easy reconfiguration
- Various interface types
- Easy cascading
- Large scale production
- Easy transmission over a long distance
- Less bandwidth usage
- Easy multi-directional transmission
- Easy translation ability
- Universal compatibility
- Easy implementation of mathematical processing algorithms and
- Standard hardware support.
- Needs anti-aliasing filter
- Higher power dissipation
- Higher learning curve is needed to program applications
- Expensive for small applications
- Possibility of downgrading the quantity of data and
- Needs a synchronized communication system to detect signals.
What is the Execution Speed of DSP?
Ideally, all Digital Signal Processors are fast but different DSPs may have different operating speeds.
Normally, these can process anywhere from 4 to 400 instructions or clock cycles. The best way to know the speed of a DSP is to consider the benchmarks.
Just like the microcontrollers, the DSPs also operate by manipulating the binary data of the device in order to improve or modify the signals.
Therefore, the main function of the DSP is to convert typical analog signals into digital format and compress them.