Digital Signal Processing MATLAB Projects Ideas - MATLAB Solutions

Construct and verify a Program Address Generator (PAG) for a 24-bit Harvard-architecture RISC DSP processor managing stack pointer, status register, and hardware loops.

• Problem & Objective: Design a hardware loop and jump-instruction fetch engine with zero-overhead loop control for RISC DSP execution pipelines.
• Key MATLAB Functions: fi, bitget, bitset, fixedpoint
• Expected Output/Metrics: Pipeline execution cycle latency plots, instruction cycle efficiency gains (>20%), and state machine transition diagrams.

Design an 8-band graphic equalizer (20Hz–3kHz) and real-time audio effects including distortion, echo, reverb, chorus, and flanger targeted for DSP hardware evaluation.

• Problem & Objective: Implement real-time discrete-time audio filtering and delay-line modulation effects with low latency.
• Key MATLAB Functions: designfilt, audioread, audioDeviceWriter, dsp.Delay
• Expected Output/Metrics: Frequency response plots across 8 equalizer bands, delay time tracking curves, and audio SNR > 85 dB.

Analyze sound barrier performance using short-time psychoacoustic parameters: loudness, sharpness, roughness, fluctuation strength, and annoyance index.

• Problem & Objective: Evaluate acoustic comfort improvements beyond sound pressure level (dBA) using non-stationary psychoacoustic algorithms.
• Key MATLAB Functions: acousticLoudness, acousticSharpness, stft, knnsearch
• Expected Output/Metrics: Annoyance index reduction (>30%), psychoacoustic spectrograms, and background noise isolation ratios.

Simulate radar pulse generation, platform velocity modeling, matched filtering, and Range-Doppler / Backprojection SAR image reconstruction algorithms.

• Problem & Objective: Synthesize high-resolution 2D radar ground imagery from raw phase-history return signals in all-weather conditions.
• Key MATLAB Functions: phased.LinearFMWaveform, matchedFilter, fft2, ifft2, imagesc
• Expected Output/Metrics: Azimuth/range spatial resolution (< 1m), point spread function (PSF) plots, and target reflectivity heatmaps.

Multi-channel acoustic sensing system processing body sounds through spatial filtering, adaptive noise reduction, and spectral cardiac feature extraction.

• Problem & Objective: Enhance heart and lung acoustic signals while attenuating ambient friction noise using multi-microphone array processing.
• Key MATLAB Functions: butter, filtfilt, pwelch, spectrogram
• Expected Output/Metrics: Signal-to-noise ratio enhancement (>15 dB), S1/S2 heart sound detection accuracy (>94%), and clean frequency spectrum plots.

Real-time fundamental frequency tracking and monophonic pitch detection converting vocal or instrumental audio into standardized MIDI musical scores.

• Problem & Objective: Estimate fundamental frequency (F0) using autocorrelation and YIN pitch extraction algorithms to output real-time MIDI note events.
• Key MATLAB Functions: pitch, xcorr, midimsg, writeMIDI
• Expected Output/Metrics: Pitch tracking accuracy (>96%), note onset timing jitter < 10ms, and exported MIDI file verification.

Comparative trade-off evaluation of parallel adders (Carry-Lookahead, Brent-Kung) and multipliers (Booth, Wallace Tree) implemented in DSP arithmetic units.

• Problem & Objective: Evaluate latency, chip area, and dynamic power consumption trade-offs in high-speed binary multiplier-accumulator (MAC) architectures.
• Key MATLAB Functions: fi, quantize, fixedpoint, bitshift
• Expected Output/Metrics: Critical path delay comparison, gate count estimation, and word-length precision quantization error plots.

Development of a real-time ultrasound/diagnostic image reconstruction platform using spatial filtering, contrast enhancement, and despeckling algorithms.

• Problem & Objective: Suppress speckle noise in low-cost real-time medical imaging systems while sharpening anatomical boundary definition.
• Key MATLAB Functions: medfilt2, histeq, edge, imcontrast
• Expected Output/Metrics: Contrast-to-noise ratio (CNR) improvement (>25%), frame rate execution > 30 FPS, and edge preservation index > 0.85.

Equalization of swept-tone (chirp) acoustic stimuli and deconvolution processing for cochlear hearing screening and Otoacoustic Emission (OAE) detection.

• Problem & Objective: Equalize acoustic chirp stimulus across ear canal frequency responses and extract minute cochlear OAE responses via deconvolution.
• Key MATLAB Functions: chirp, deconv, tfestimate, audioread
• Expected Output/Metrics: OAE response magnitude boost (+6 dB compared to click stimuli), flat stimulus ear canal calibration (±1 dB), and SNR > 20 dB.