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DSP based Projects
By doing project in DSP one
can learn skill on the following areas, Discrete time signals,
Generate FIR and IIR filters, DSP Image processing, Demonstrate
the multi-rate and adaptive signal processing concepts.
Auto correlations and cross
correlation, Frequency Analysis using DFT, Design of FIR filters,
Design butterworth Filter and many more simulations works.
Digital
Signal Processing using MATLAB:
1. Audio
Signal Noise Reduction
Objective:
Design a MATLAB-based system to reduce noise in an audio signal
using filters.
Techniques:
Low-pass, high-pass, band-pass, and notch filters, Fast Fourier
Transform (FFT), wavelet transform.
Outcome:
A system that can remove noise from an audio file, improving its
clarity without distorting the original signal.
2.
Real-time Signal Processing
Objective:
Implement real-time signal processing in MATLAB to process audio
or sensor signals in real-time.
Techniques:
Real-time data acquisition, filtering, and analysis using
MATLAB’s DSP System Toolbox.
Outcome:
A real-time DSP system that can be used for applications like
audio equalization or sensor data monitoring.
3. Digital
Image Processing
Objective:
Develop an image processing system in MATLAB to enhance images,
detect edges, or perform image segmentation.
Techniques:
Spatial filtering, Fourier transform, histogram equalization,
edge detection algorithms (e.g., Sobel, Canny).
Outcome:
An image processing application that can improve image quality
or identify features within an image.
4. Speech
Recognition System
Objective:
Create a basic speech recognition system using DSP techniques in
MATLAB.
Techniques:
Feature extraction (e.g., Mel-frequency cepstral coefficients),
pattern recognition algorithms, Hidden Markov Models (HMM).
Outcome:
A system that can recognize simple spoken words or commands,
useful for voice-controlled applications.
5. Design
of FIR and IIR Filters
Objective:
Design and analyze Finite Impulse Response (FIR) and Infinite
Impulse Response (IIR) filters using MATLAB.
Techniques:
Filter design methods like windowing, frequency sampling for
FIR, and bilinear transformation for IIR, filter performance
analysis.
Outcome:
A set of optimized filters that meet specific criteria for
passband, stopband, and transition bandwidth.
6.
Modulation and Demodulation Techniques
Objective:
Implement and analyze various modulation and demodulation
techniques (AM, FM, QAM, PSK) using MATLAB.
Techniques:
Simulate modulation and demodulation processes, analyze signal
spectrum, bit error rate (BER) analysis.
Outcome:
A MATLAB model that can simulate and analyze different
modulation techniques used in communication systems.
7. Design
of Adaptive Filters
Objective:
Design adaptive filters using algorithms like LMS (Least Mean
Squares) or RLS (Recursive Least Squares) in MATLAB.
Techniques:
Implement adaptive filtering for applications like noise
cancellation or echo suppression.
Outcome:
An adaptive filter that automatically adjusts its parameters to
minimize the error signal in dynamic environments.
8. Image
Compression using DCT
Objective:
Develop an image compression system using the Discrete Cosine
Transform (DCT) in MATLAB.
Techniques:
Implement DCT-based compression, analyze compression ratio, and
image quality (e.g., PSNR).
Outcome:
A MATLAB tool that compresses images effectively while
maintaining acceptable quality.
9. Spectral
Analysis of Signals
Objective:
Perform spectral analysis of signals using MATLAB to identify
frequency components.
Techniques:
Fourier transform (FFT), power spectral density (PSD)
estimation, windowing techniques.
Outcome:
A MATLAB application that can analyze and display the spectral
content of various signals (e.g., audio, communication signals).
10. ECG
Signal Analysis
Objective:
Analyze Electrocardiogram (ECG) signals to detect abnormalities
like arrhythmia or heart rate variability using MATLAB.
Techniques:
Signal filtering, feature extraction, R-peak detection,
time-frequency analysis.
Outcome:
A MATLAB-based diagnostic tool that can assist in the analysis
of ECG signals, potentially aiding in early detection of cardiac
issues.
DSP trainer
kit mini projects
Using a DSP
trainer kit, typically involving basic signal processing
operations, filter design, modulation techniques, and more. These
exercises are designed to help students and engineers get
hands-on experience with DSP concepts:
1. Basic
Signal Generation and Analysis
Exercise:
Generate different types of signals (sine, square, triangular,
and sawtooth) using the DSP trainer kit.
Tasks:
Observe the
waveforms on an oscilloscope or through the trainer kit’s
display.
Measure and
analyze the frequency, amplitude, and phase of each signal.
Objective:
Understand basic signal characteristics and how they can be
manipulated in the digital domain.
2. Discrete
Fourier Transform (DFT) and FFT
Exercise:
Implement and observe the Discrete Fourier Transform (DFT) and
Fast Fourier Transform (FFT) on a signal.
Tasks:
Apply DFT
and FFT to a given input signal (e.g., sine wave with added
noise).
Analyze the
frequency components of the signal.
Compare the
efficiency and accuracy of DFT and FFT.
Objective:
Learn how to convert time-domain signals to the frequency domain
and understand the importance of FFT in DSP.
3. Digital
Filtering (FIR and IIR Filters)
Exercise:
Design and implement FIR (Finite Impulse Response) and IIR
(Infinite Impulse Response) filters on the DSP trainer kit.
Tasks:
Use the kit
to create low-pass, high-pass, band-pass, and notch filters.
Test the
filters with different input signals (e.g., noise, sinusoidal
signals).
Observe the
output waveform and analyze the filter’s performance.
Objective:
Gain practical knowledge of filter design and understand the
difference between FIR and IIR filters.
4. Signal
Convolution
5. Signal
Modulation and Demodulation
Exercise:
Implement amplitude modulation (AM) and frequency modulation
(FM) using the DSP trainer kit.
Tasks:
Modulate a
baseband signal using AM and FM techniques.
Demodulate
the signal and observe the recovered signal.
Analyze the
effects of modulation depth and frequency deviation.
Objective:
Learn the principles of modulation and demodulation, which are
fundamental in communication systems.
6. Sampling
and Reconstruction
7.
Quantization and Signal Compression
Exercise:
Implement quantization and signal compression techniques.
Tasks:
Quantize an
analog signal to different bit levels (e.g., 8-bit, 16-bit).
Observe the
quantization noise and its effect on signal quality.
Apply basic
compression techniques and analyze the trade-offs between
compression ratio and signal quality.
Objective:
Learn about the process of analog-to-digital conversion, the
effects of quantization, and the basics of signal compression.
8. Adaptive
Filtering
Exercise:
Implement an adaptive filter (e.g., LMS algorithm) on the DSP
trainer kit.
Tasks:
Design an
adaptive noise cancellation system.
Test the
system with a noisy input signal and observe the filter’s
ability to adapt and minimize the noise.
Analyze the
convergence speed and stability of the adaptive filter.
Objective:
Explore adaptive filtering techniques and their applications in
noise cancellation and echo suppression.
9. Wavelet
Transform
10. Speech
Signal Processing
Exercise:
Process and analyze speech signals using the DSP trainer kit.
Tasks:
Record and
process a speech signal (e.g., apply filtering, FFT).
Implement
basic speech compression or enhancement techniques.
Analyze the
speech signal’s formants and pitch using spectral
analysis.
Objective:
Explore DSP applications in speech processing, including
enhancement, compression, and analysis.
These
exercises provide a solid foundation in digital signal processing
and help bridge the gap between theoretical concepts and
practical applications. The use of a DSP trainer kit allows you
to visualize and experiment with real signals, deepening your
understanding of DSP principles.
B.E ECE / EEE/ EIE Final year
DSP
Project Titles
From DSP projects you can
learn to carry basic DSP operations, Improve the ability to use
MATLAB for signal processing , Design applications using DSP
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3D
Synthetic Environment
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A
High Performance Implementation of MPEG-1 Layer 3 Audio Encoder
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AC
drive
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Acoustic
Echo Cancellation algorithm & Implementation Using DSP
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Acoustic
liquid level gauge
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Adaptive
channel equalization
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Advanced
LCR meter using DSP techniques
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ALU
design using VHDL
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Audio
signal processing
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Automatic
collision avoider
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Binaural
sound localization
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Biologically
plausible pitch perception
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Biometric
finger print system
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Biometrics
smart camera
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Cellular
communication simulator by using MATLAB
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Channel
Implementation
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Character
display
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Class
5 accuracy data actuation
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Cochlea
Implants
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Command
and control using voice recognition
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Counter
design
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CPU
design
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Data
compression
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Data
transmission through power line
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Delta
modulation
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Detection
of Human Speech in Structured Noise
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Digital
AC Motor Control
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Digital
Scanner
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Digital
signal processing aid for labs
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Digital
signals processing demonstrator
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Doppler
correction
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DSP
based data acquisition system
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DSP
based digital equalizer
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DSP
based ECG monitor
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DSP
based image processing
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DSP
based karaoke system
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DSP
based medical announcement system
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DSP
based modems
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DSP
based multi channel monitoring system
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DSP
based signal analyzer
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DSP
based voice transmission system
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DSP
function generator
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DTMF
code generator & detection
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Error
correction coding using convolution encoding and VITERBI
decoding
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Error
correction coding using trellis encoding and VITERBI decoding
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Estimation
of aircraft trajectory from its motion using KALMAN TRACKING
FILTER
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Estimation
of energy using sub band coding
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FFT
design
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FIR
& IIR filters design
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FSK
modulation & demodulation
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Function
generator
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Implementation
of GMSK modem using Matlab
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Implementation
of OFDM with variable data sets using Matlab GUI
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Multiuser
Detection in DS-CDMA using MMSE approach
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DTMF
detection using Goertzel algorithm with Matlab GUI
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Implementation
Cellular Is-95 standard in CDMA systems
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Higher
Order SVD for dynamic texture analysis in video
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Adaptive
Bilateral filter for sharpness enhancement and noise removal
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Blind
self authentication of images for robust watermarking using IWT
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Comparision
and improvement of wavelet based image fusion
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Weighted
Adaptive Lifting based wavelet transform for image coding
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A
spatial Median Filter for noise removal
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Contourlet
based image watermarking using optimum detector in noisy
environment
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Wavelet
based palm print authentication system
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A
CMOS image sensor with focal plane SPIHT image compression
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A
visual information encryption scheme based on visual
cryptography using DH method
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Low
power variable block size motion estimation using pixel
truncation
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Expansion
embedding techniques for Reversible watermarking
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Steganography
using BPCS to the IWT image
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Reconstruction
of under water image by bi-spectrum
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Wavelet
based image authentication and recovery
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Natural
image compression based on modified SPIHT (Wavelet packets)
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Image
blur reduction for cell cameras via adaptive tonal correction
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Video
surveillance with sum of absolute differences
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Content
based image retrieval with realistic color images
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Implementation
of IRIS Recognition system using HOUGH transforms
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Facial
recognition system using PCA Analysis
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Effective
Fuzzy C means clustering algorithm for MRI Brain tumour
detection
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ECG
signal denoising and baseline wander correction using empirical
mode decomposition
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A
wavelet based denoising technique for Ocular arti-fact
correction of the EEG Signal
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Acoustic
echo cancellation tolerable for double talk
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A
variable step size affine projection algorithm designed fro
acoustic echo cancellation
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Variable
step size NLMS algorithm for under modelling acoustic echo
cancellation
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Adaptive
algorithm for speech compression using discrete cosine packet
transforms
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Warped
DCT based noisy speech enhancement
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Robust
adaptive kalman filtering based speech enhancement algorithm
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An
adaptive KLT approach for speech enhancement
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Speech
compression using LPC/DWT
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Speech
enhancement using adaptive wiener Filter
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Content
based Speech watermarking using DWT
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Analyzing
equalizer effects for a speech signals
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An
improved visual cryptography for secret hiding
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Curved
wavelet transform for image coding
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Sliced
Ridge let transform for image Denoising
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Low
complexity multi resolution image codec using lifting wavelet
transform
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Lossless
compression of color map images by context tree modelling
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Extended
JPEG 2000 image compression systems
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Data
embedding scrambled digital video
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Block
Matching algorithm motion estimation for video codec
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A
high performance JPEG 2000 architecture
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Video
watermarking using discrete wavelet transforms
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Morphological
processing for color images
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Implementation
and analysis of Wide Band CDMA systems
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An
efficient Resource allocation strategy for future wireless
cellular systems
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Time-Domain
signal detection using second order statistics for MIMO-OFDM
systems
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Pre
DFT processing for MIMO OFDM systems with space time frequency
coding
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Channel
estimation and prediction for adaptive OFDM downlinks
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Maximum
Likelihood carrier frequency offset estimation for OFDM systems
in fading channels
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Channel
Estimation and prediction for adaptive OFDMA/TDMA uplinks based
on non overlapping pilot signals
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Downlink
BER simulation for IEEE 802.16e OFDM physical layer
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Channel
Code tracking in wireless OFDM Systems
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Performance
analysis of IEEE 802.11a physical layer
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An
Affine combination two LMS adaptive Filters Transient Mean
Square Analysis
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A
Time Varying Convergence parameter for LMS Algorithm in the
presence white Gaussian noise
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Robust
control approach to perfect reconstruction of digital signals
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Non
parametric Linear time invariant system identification by DWT
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Adaptive
DS-CDMA Receiver with code tracking in unknown phase
environments
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Multi
user detection in CDMA systems using PDA algorithm under AWGN
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Performance
analysis of Iterative channel estimation and multi user
detection in multi user CDMA System
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A
Full rank regularization technique for MMSE detection in Multi
user CDMA systems
DSP project Kits Price list
1.
TMS320C6713 DSP Starter Kit
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Includes: Texas
Instruments TMS320C6713 floating-point DSP, audio
interfaces, onboard codec, and power supply.
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Price: ₹15,000 – ₹25,000
2.
TMS320C6748 DSP Development Kit
3.
DSPIC30F4011 Trainer Kit
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Includes: Microchip
DSPIC30F4011 16-bit DSC, ADC, DAC, motor control
interface, and LCD interface.
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Price: ₹6,000 – ₹10,000
4.
TMS320C28346 DSP Trainer Kit
5.
Analog Devices ADSP-21489 EZ-KIT Lite
6.
DSPIC33F Microcontroller Development
Kit
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Includes: DSPIC33F 16-bit
DSC, UART, ADC, PWM control, and LCD interface.
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Price: ₹7,000 – ₹12,000
7.
TMS320C5416 DSP Trainer Kit
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Includes: TMS320C5416 DSP
processor, built-in audio codec, high-speed data
processing interface, and power supply.
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Price: ₹12,000 – ₹18,000
8.
ADSP-BF533 EZ-KIT Lite
9.
TMS320F28379D DSP Development Kit
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Includes: TMS320F28379D
DSP, built-in communication modules (CAN, I2C, SPI), and
real-time processing capabilities.
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Price: ₹15,000 – ₹25,000
10.
Xilinx FPGA DSP Development Kit
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