DSP IEEE 2018 Projects @ Chennai

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Cooperative Spectrum Sensing in Cognitive Radio Networks with Kernel Least Mean Square

To design different adaptive filter (LMS, RLS NLMS, KLMS KRLS, Kalman Filter
Kalman, and EKF)
Fig.3 Learning curves of KLMS, NLMS, LMS, RLS, KRLS, Kalman
Fig.4 Probability of detection for (KLMS, NLMS, LMS, RLS, KRLS, Kalman,) and three other decision fusion methods: AND, OR, and Majority Rules.
Fig. 5. Probability of Detection for different users SNR and user numbers for:
A.    KLMS
B.    LMS
C.    NLMS
D.    RLS
E.    KRLS
F.    KalmanFilter

Spectrum sensing is a key technology in cognitive radio networks to detect the unused spectrum. Cooperative spectrum sensing scheme is widely employed due to its quick and accurate performance. In this paper, a new cooperative spectrum sensing by using Kernel Least Mean Square (KLMS) algorithm is proposed for the case where each secondary user (SU) makes a binary decision based on its local spectrum sensing using energy detection, and the local decisions are sent to a fusion center (FC), where the final decision is made on the spectrum occupancy status. In our approach, the KLMS is utilized to enhance the reliability of the final decision. Since KLMS performs well in estimating a complex nonlinear mapping in an online manner, the proposed method can track the changing environments and enhance the reliability of decisions in FC. The desirable performance of the new fusion scheme is confirmed by Monte-Carlo simulation results

Matlab Code:

clc
clear all
close all
%%

klen=10;
len_time=100;
ori_signal=[];
noise_data=[];
signal_data=[];
for snr_db=[10];
   
    snr = 10.^(snr_db./10); % SNR in linear scale
    mess_data=randi([0 1],klen,len_time);
    mod_data=(2.*(mess_data)-1);
    noise_gen_data=randn(klen,len_time); % Gaussian noise, mean 0, variance 1
    ori_signal=[ori_signal sqrt(snr).*mod_data+noise_gen_data];
    noise_data=[noise_data noise_gen_data];
   
    signal_data=[signal_data mod_data];
end
len_time=length(ori_signal);


%% NLMS mu 0.2
srtleg{1}='NLMS';
propval=0.1;
weight_value=ones(klen,len_time);
muval=0.2;
for prop_fals=propval
    threshold_value=qfuncinv(prop_fals);
    for kiter=1:len_time
        ddata=ori_signal(:,kiter);
      
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
        sn=weight_value(:,kiter)'*ddatax;
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-sn;
        weight_value(:,kiter+1)=weight_value(:,kiter)+muval*en*(ddatax/(ddatax'*ddatax));
        msevalue_pro(kiter)=mean(weight_value(:,kiter).^2);
    end
   
end
figure,plot(msevalue_pro,'r')
xlabel('time');
ylabel('mse');

%% LMS mu 0.2
srtleg{2}='LMS';
weight_value=ones(klen,len_time);
muval=0.2;
for prop_fals=propval
    threshold_value=qfuncinv(prop_fals);
    for kiter=1:len_time
        ddata=ori_signal(:,kiter);
       
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
        sn=weight_value(:,kiter)'*ddatax;
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-sn/2;
        weight_value(:,kiter+1)=weight_value(:,kiter)+muval*en*(ddatax);
        msevalue_pro(kiter)=mean(weight_value(:,kiter).^2);
    end
   
end
hold on,plot(msevalue_pro,'g')
xlabel('time');
ylabel('mse');


%% KLMS mu 0.2
srtleg{3}='KLMS';
weight_value=ones(klen,len_time);
muval=0.2;
for prop_fals=propval
    threshold_value=qfuncinv(prop_fals);
    for kiter=1:len_time
        ddata=ori_signal(:,kiter);
       
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
        sn=weight_value(:,kiter)'*ddatax;
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-sn/8;
        kerval=kernal_func(ddatax);
        weight_value(:,kiter+1)=weight_value(:,kiter)+muval*en*(kerval);
        msevalue_pro(kiter)=mean(weight_value(:,kiter).^2);
    end
   
end
hold on,plot(msevalue_pro,'k')
xlabel('time');
ylabel('mse');


%% RLS
srtleg{4}='RLS';
lamda = 0.999 ;       
delta = 1e1 ;       
rls_para=delta*eye (klen) ;
weight_value=ones(klen,len_time);

for prop_fals=propval
    threshold_value=qfuncinv(prop_fals);
    for kiter=1:len_time
        ddata=ori_signal(:,kiter);
       
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
       
        phval_data=weight_value(:,kiter)'*rls_para;
        kdata = phval_data'/(lamda + phval_data * weight_value(:,kiter) );
        sn=weight_value(:,kiter)'*ddatax;
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-sn/3;
        weight_value(:,kiter+1)=weight_value(:,kiter)+kdata*en;
        rls_para = ( rls_para - kdata * phval_data ) / lamda ;
        msevalue_pro(kiter)=mean(weight_value(:,kiter).^2);
    end
end
hold on,plot(msevalue_pro,'b')
xlabel('time');
ylabel('mse');


%% KRLS
srtleg{5}='KRLS';
lamda = 0.999 ;       
delta = 1e2 ;       
rls_para = delta * eye (klen) ;
weight_value=ones(klen,len_time);
for prop_fals=propval
    threshold_value=qfuncinv(prop_fals);
    for kiter=1:len_time
        ddata=ori_signal(:,kiter);
       
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
       
        phval_data=weight_value(:,kiter)'*rls_para;
        kdata=phval_data'/(lamda+phval_data*weight_value(:,kiter) );
        sn=weight_value(:,kiter)'*ddatax;
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-sn/4;
        kerval=kernal_func(kdata);

        weight_value(:,kiter+1)=weight_value(:,kiter)+kerval*kdata*en;
      
        rls_para = ( rls_para - kdata * phval_data ) / lamda ;
        msevalue_pro(kiter)=mean(weight_value(:,kiter).^2);
    end
   
end
hold on,plot(msevalue_pro,'y')
xlabel('time');
ylabel('mse');



%% Kalman filter
srtleg{6}='kalman';
weight_value=ones(klen,len_time);
for prop_fals=propval
    threshold_value=qfuncinv(prop_fals);
    for kiter=2:len_time
        ddata=ori_signal(:,kiter);
      
       
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
      
        ddatap=ori_signal(:,kiter-1);
        ddata1p=(abs(ddatap).^2)>threshold_value;
        ddataxp=2*ddata1p-1;
        sn=weight_value(:,kiter)'*ddatax+weight_value(:,kiter-1)'*ddataxp;
       
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-(sn/8);
        weight_value(:,kiter+1)=weight_value(:,kiter)+en*(ddatax/(ddatax'*ddatax));
       msevalue_pro(kiter)=mean(weight_value(:,kiter).^2); 
    end
   
end
hold on,plot(msevalue_pro,'g:','linewidth',3)
xlabel('time');
ylabel('mse');

%%  eKF
srtleg{7}='EKF';
weight_value=ones(klen,len_time);
for prop_fals=propval
    threshold_value=qfuncinv(prop_fals);
    for kiter=2:len_time
        ddata=ori_signal(:,kiter);
       
       
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
      
        ddatap=ori_signal(:,kiter-1);
        ddata1p=(abs(ddatap).^2)>threshold_value;
        ddataxp=2*ddata1p-1;
      
       
       
        sn=weight_value(:,kiter)'*ddatax+weight_value(:,kiter-1)'*ddataxp;
       
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-(sn/16);
       
        weight_value(:,kiter+1)=weight_value(:,kiter)+en*(ddatax/(ddatax'*ddatax));
        msevalue_pro(kiter)=mean(weight_value(:,kiter).^2);
    end
   
end
hold on,plot(msevalue_pro,'m-')
xlabel('time');
ylabel('mse');
grid on;
axis([1 length(msevalue_pro) 0 1]);
legend(srtleg,'location','best');


A Novel Adaptive Fusion Scheme for Cooperative Spectrum Sensing Paper

A Novel Adaptive Fusion Scheme for Cooperative Spectrum Sensing Paper

This is open
This Paper is implemented for RLS and NLMS.In cognitive radio systems, the accuracy of spectrum
sensing depends on the received primary signal strength at the secondary user (SU). In fact, a single node sensing would be compromised if the received signal strength is not high enough to be detected by this node. In this paper, we propose a cooperative decision fusion rule based on adaptive linear combiner. The weights which correspond to confidence levels affected to SUs, are determined adaptively using the Normalized Least Mean Squares (NLMS) and the Recursive Mean Squares (RLS) algorithms. The proposed algorithms combine the SUs decisions with the adaptive confidence levels to track the surrounding environment.

Proposal Work:

To implement the paper by NLMS, LMS RLS, KRLS, Kalman Filter, EKF Filter.

Figure (3): Mean of the confidence level vector versus time (K = 3):

a)     NLMS algorithm

b)    KLMS algorithm

c)     LMS algorithm

d)    RLS algorithm

e)     KRLS Algorithm

f)     Kalman Filter

g)    EKF Algorithm


Fig. 4. MSD versus. for

a)     NLMS algorithm

b)    KLMS

c)     LMS

d)    RLS

e)     KRLS

f)     Kalman Filter

g)    EKF

Fig. 5. Performance of the proposed approach:

a)     Qd and versus time (K = 10) for (NLMS, LMS, KLMS, RLS, KRLS, Kalman, EKF, OR Rule)

b)     Qf versus time (K = 10). for (NLMS, LMS, KLMS, RLS, KRLS, Kalman, EKF, OR Rule

c)     Qd versus time (K = 10).  for (NLMS, LMS, KLMS, RLS, KRLS, Kalman, EKF, AND Rule.

d)    Qf versus time (K = 10).  for (NLMS, LMS, KLMS, RLS, KRLS, Kalman, EKF, AND Rule.

e)     Qd and versus time (K = 10) for (NLMS, RLS, LMS, KRLS, Kalman, EKF, Majority Rule)

f)     Qf versus time (K = 10). For (NLMS, KLMS, LMS, RLS, KRLS, Kalman, EKF, Majority Rule)

Fig. 6. ROC curves (K = 10 and Pf = 0.1). For all adaptive proposed schemes.

Fig. 7. Received SNR at the 1st SU changes (K = 3 and Pf = 0.1) for all adaptive filter (NLMS, LMS, KLMS, RLS, KRLS, Kalman Filter, EKF Filters)

Fig. 8. PU status changes (K = 10 and Pf = 0.1) for all adaptive filter (NLMS, LMS, KLMS, RLS, KRLS, Kalman Filter, EKF Filter)


Matlab Code


clc
clear all
close all
%%

klen=10;
len_time=100;
ori_signal=[];
noise_data=[];
signal_data=[];
for snr_db=[10];
   
    snr = 10.^(snr_db./10); % SNR in linear scale
    mess_data=randi([0 1],klen,len_time);
    mod_data=(2.*(mess_data)-1);
    noise_gen_data=randn(klen,len_time); % Gaussian noise, mean 0, variance 1
    ori_signal=[ori_signal sqrt(snr).*mod_data+noise_gen_data];
    noise_data=[noise_data noise_gen_data];
   
    signal_data=[signal_data mod_data];
end
len_time=length(ori_signal);


%% NLMS
srtleg{1}='NLMS';
propval=0.1;
ind=1;
for muval=0.1:0.1:2
   
threshold_value1=qfuncinv(0.1);

for prop_fals=propval
    weight_value=ones(klen,len_time);
    threshold_value=qfuncinv(prop_fals);
    for kiter=1:len_time
        ddata=ori_signal(:,kiter);
        Weigth1n_value(kiter)=mean(weight_value(:,kiter));
        ddata1=(abs(ddata).^2)>threshold_value;
        ddatax=2*ddata1-1;
        sn=weight_value(:,kiter)'*ddatax;
        res=ddata1(1);
        for k3=2:length(ddata1)
            res=bitor(ddata1(k3),res);
        end
        desrval=res*2-1;
        en=desrval-sn;
        weight_value(:,kiter+1)=weight_value(:,kiter)+muval*en*(ddatax/(ddatax'*ddatax));
       
    end
   
    
msdval(ind)=10*log10(mean((Weigth1n_value-mean(Weigth1n_value)).^2));
muvalfinal(ind)=muval;
ind=ind+1;

end

end
figure,plot(muvalfinal,msdval,'r-s');
xlabel('mu');
ylabel('MSD(db)');
grid on;
title('Mean Square Deviation');
%%


MATLAB IEEE 2017 PROJECTS

COMMUNICATION TOPICS

Year 2007
  • An OFDM-CDMA scheme for High Data Rate UWB applications
  • Time-Domain Signal Detection Based on Second-Order Statistics for MIMO-OFDM Systems.
  • Sequence Synchronization in a wideband CDMA  System
Year 2008
  • A Token-Based Scheduling Scheme for WLANs Supporting Voice/Data Traffic and its Performance Analysis
  • Adaptive Radio Resource Allocation for Downlink OFDMA/SDMA Systems with Multimedia Traffic
  • Coding Schemes Applied to Peak-to-Average Power Ratio (PAPR) Reduction in OFDM Systems
  • Cooperative Sensing for Primary Detection in Cognitive Radio
  • Design and Analysis of Bit Interleaved Coded Space-Time Modulation
  • Enhancing MB-OFDM Throughput with Dual Circular 32-QAM
  • Fast and Efficient QoS-Guaranteed Adaptive Transmission Algorithm in the Mobile WiMAX System
  • Filter Bank Spectrum Sensing for Cognitive Radios
  • Joint Optimum Linear Precoding and Power Control Strategies for Downlink MC-CDMA Systems
  • Efficient Spatial Covariance Estimation for Asynchronous Co-channel Interference Suppression in MIMO-OFDM Systems
  • Power Allocation for Two Different Traffics in Layered MIMO Systems
  • Performance Evaluation of the WiMedia PHY in WPAN Environments and Efficiency Improvement by Application of LDPC Codes
  • Variable Sub-carrier in OFDM to Reduce the ICI Due to Carrier Frequency Offset and IQ Imbalance
Year 2009
  • Ranging With Ultrawide Bandwidth Signals in Multipath Environments
  • Semisoft Handover Gain Analysis Over OFDM-Based Broadband Systems
  • Ultra-Wide-Band Propagation Channels
  • Pulsed-OFDM Modulation for Ultrawideband Communications
  • Grouping Technique for Cooperative Spectrum Sensing in Cognitive Radios
  • Implementation of the least squares channel estimation algorithm for MIMO-OFDM systems
  • Sequential Detection for Multiuser MIMO CDMA Systems with Single Spreading Code Per User
  • A Multicode Approach for High Data Rate UWB System Design
  • Replacement of Spectrum Sensing in Cognitive Radio
  • Variance-Reduced Partial Parallel Interference Cancellation for MC-CDMA Uplink Systems
  • A Closed-Form Blind CFO Estimator Based on Frequency Analysis for OFDM Systems
  • Eigenvalue based Spectrum Sensing Algorithms for Cognitive Radio
  • A New Parameter for UWB Indoor Channel Profile Identification
  • Cognitive Radio Sensing Architecture and A Sensor Selection Case Study
  • Cooperative Spectrum Sensing with Cluster-Based Architecture in Cognitive Radio Networks
  • Efficient Power Allocation for Coded OFDM Systems
  • Measurement Based Channel-Adaptive Video Streaming for Mobile Devices over Mobile WiMAX
  • Sparsity-Embracing Multiuser Detection for CDMA Systems with Low Activity Factor
  • Analysis and Comparison of Clipping Techniques for OFDM Peak-to-Average Power Ratio Reduction
  • Error control coding in wireless sensor networks
Year 2010
  • Bandwidth Exchange: An Energy Conserving Incentive Mechanism for Cooperation
  • Blind Matched Filtering for Multiple Input Multiple Output Transceivers
  • Estimation of Cubic Nonlinear Bandpass Channels in Orthogonal Frequency-Division Multiplexing Systems
  • Error-Resilient H.264/AVC Video Transmission Using Two-Way Decodable Variable Length Data Block
  • Simplified Multiaccess Interference Reduction for MC-CDMA With Carrier Frequency Offsets
  • Optical Communications Performance of Hybrid 34-Meter Microwave Antennas
  • Performance Analysis of Distributed Decision Fusion Using A Censoring Scheme in Wireless Sensor Networks
  • Gradient Descent Bit Flipping Algorithms for Decoding LDPC Codes
  • Efficacy of Multiband OFDM Approach in High Data Rate Ultra WideBand WPAN Physical Layer Standard using Realistic Channel Models
  • Carrier Frequency Offsets Problem in DCT-SC-FDMA System
  • Signal to Interference Ratio Based Handoff Management for Next-Generation Wireless Systems
  • Anti-Phishing detection of phishing attacks using Genetic Algorithm
  • Convolutional Codes in Two Way Relay Networks with Physical-Layer Network Coding
Year 2011
  • Low complexity PTS algorithm based on gray code and its FPGA implementation
  • Performance Analysis of MIMO-OFDM System Using QOSTBC Code Structure for M-QAM
  • Dynamic Dwell Timer for Hybrid Vertical Handover in 4G Coupled Networks
  • Exploiting Sparse User Activity in Multiuser Detection
  • IIR system identification using cat swarm optimization
  • Peak to Average Power Ratio (PAPR) Reduction in OFDM for a WLAN network Using SLM Technique
  • Suppression of Narrowband Interference in impulse radio based high data rate UWB WPAN communication system using NLOS Channel Model
  • Digital Fractional Order Savitzky-Golay Differentiator
  • A New Algorithm for Power Allocation in  MIMO-OFDM Systems  with a Beam-forming Scheme
  • Poly:A reliable and energy efficient topology control protocol for wireless
  • High user capacity collaborative code-division multiple access  
  • Phishing Website Detection and Optimization using Particle Swarm Optimization
Year 2012
  • Analysis and Design of Coding and Interleaving in a MIMO-OFDM Communication System
  • Optimum Clustered Pilot Sequence for OFDM Systems under Rapidly Time-Varying Channel
  • Performance Evaluation of Complex Wavelet Packet Modulation (CWPM) System over Multipath Rayleigh Fading Channel
  • Two-Way Amplify-and-Forward MIMO Relay Networks with Antenna Selection
  • A Frequency Offset Estimation and Compensation Scheme for  MB-OFDM UWB Modem 
  • Analysis and Design of Coding and Interleavingin a MIMO-OFDM Communication System  
  • Anti-Phishing Techniques:A Review 
  • Robust Fast Time-Varying Multipath Fading Channel  Estimation and Equalization for MIMO-OFDM Systems via Fuzzy Method
  • Design of frequency response masking FIR filter in the Canonic Signed Digit space using modified ABC Algorithm
Year 2013
  • Adaptive resource allocation for downlink grouped MC-CDMA systems with power and BER constraints
  • Selfish Attacks and Detection in Cognitive Radio Ad-Hoc Networks
  • An Evolving Graph-Based Reliable Routing Scheme for VANETs
  •  An Incremental Hop Selection Scheme for Amplify-and-Forward Multi-Hop Networks
Year 2014
  • A Review of Exposure and Avoidance Techniques for Phishing Attack
  • Comparative Analysis of FBMC and OFDM Multicarrier Techniques for Wireless Communication Networks
  • Review of Phishing Detection Techniques 
  • Design and Analysis of Low-Complexity Multi-Antenna Relaying for OFDM-Based Relay Networks
Year 2015 
  • Survey on Phishing Attacks 
  • Performance of two dimensional asymmetrically and symmetrically clipping optical OFDM in AWGN
  • Comparative analysis of the BER performance of DWT OFDM over that of FFT OFDM in presence of phase noise
  • OFDM-Modulated Dynamic Coded Cooperation in Underwater Acoustic Channels
  • Underwater communication implementation with OFDM
  • A Survey on Channel Estimation in MIMO-OFDM Systems
  • Relative Analysis of Transceiver Diversity and Channel Estimation of MIMO OFDM
  • On the Sum Capacity of the Gaussian X Channel inthe Mixed Interference Regime
  • Min-Max Approximation of Transfer Functions With Application to Filter Design
  • New Robust Estimators of Correlation and Weighted Basis Pursuit
  • MIO:Enhancing Wireless Communications Security Through Physical Layer Multiple Inter-Symbol Obfuscation
 Year 2016
  • Input-Based Dynamic Reconfiguration of Approximate Arithmetic Units for Video Encoding
  • Golay-Correlator Window-Based Noise Cancellation Equalization Technique for 60-GHz Wireless OFDM-SC Receiver
  • Efficient Integer Frequency Offset Estimation Architecture for Enhanced OFDM Synchronization
  • Local Spectral Component Decomposition for Multi-Channel Image Denoising
        
Others
  • McMAC: A Parallel Rendezvous Multi-Channel MAC Protocol
  • Performance of Coded Multi-Carrier DS-CDMA systems in Multi-path fading channels
  • Interference Rejection in Direct Sequence Spread Spectrum Communication Systems
IMAGE PROCESSING
  • Support vector machine based multi-view face detection and recognition-2004
  • Fingerprint Feature Extraction Based Discrete Cosine Transformation (DCT)-2006
  • Intensified fuzzy clusters for classifying plant, soil, and residue regions of interest from color images
  • Determination of Minutiae Scores for Fingerprint Image Applications
  • MRI brain image segmentation by multi-resolution edge detection and region selection
  • Recognition of human actions using motion history information extracted from the compressed video
  • Automated Classification of fMRI Data Employing Trial
  • Complex Wavelets and its application to Image Fusion
  • Genetic Algorithms for the Unsupervised Classification of Satellite Images
Year 2007
  • Color Image Segmentation Based on Mean Shift and Normalized Cuts
  • Hierarchical contour matching for dental X-ray radiographs
  • An Improving Model Watermarking with Iris Biometric Code
  • Lossless Video Sequence Compression Using Adaptive Prediction
  • A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network
Year 2008
  • Active Learning Methods for Interactive Image Retrieval
  • Detecting Dominant Motions in Dense Crowds
  • Personal Authentication Based on Iris Texture Analysis
  • Robust Image Segmentation Algorithm Using Fuzzy Clustering Based on Kernel-Induced Distance Measure
  • Wearable Monitoring of Seated Spinal Posture
  • Design of a Distributed Traffic Monitoring System and Algorithm based on Web-camera
  • VisualRank: Applying PageRank to Large-Scale Image Search
  • Watermarking Relational Databases using Optimization Based Techniques
  • Fingerprint Verification Using SIFT Features
  • A Lossless Compression Scheme for Bayer Color Filter Array Images
  • Motion-Tracking for Hands-Free Mouse-Pointer Manipulation
  • Face Tracking and Recognition with Visual Constraints in Real-World Videos
  • An a contrario approach for outliers segmentation application to multiple sclerosis in MRI
  • An Unsupervised Technique Based on Morphological Filters for Change Detection in Very High Resolution Images
  • A Novel Segmentation Algorithm for Side-scan Sonar Imagery with Multi-Object
Year 2009
  • A Fast Image Compression Algorithm Based on SPIHT
  • Application of Support Vector Machine and Genetic Algorithm for Improved Blood Cell Recognition
  • Reconstruction Of Underwater Image By BISPECTRUM
  • Combined Wavelet-Domain and Motion-Compensated Video Denoising Based on Video Codec Motion Estimation Methods
  • Artificial Neural Network Based Automatic Face Parts Prediction System from Only Fingerprints
  • A Histogram Modification Framework and Its Application for Image Contrast Enhancement
  • New Statistical Detector for DWT-Based Additive Image Watermarking Using the Gauss–Hermite Expansion
  • Fast Query Point Movement Techniques for Large CBIR Systems.
  • A Video Coding Scheme Based on Joint Spatiotemporal and Adaptive Prediction
  • The Global K-Means Algorithm for Clustering in Feature Space
  • Towards Handwritten Mathematical Expression Recognition.
  • Content-Based Classification&Segmentation of Mixed Type Audio by Using MPEG Features
  • ECG Arrhythmia Classification with Support Vector Machines and Genetic Algorithm
Year 2010
  • Face Verification across Age Progression using Discriminative Methods
  • Frequency Compounding for Ultrasound Freehand Elastography
  • Satellite Image Resolution Enhancement Using Complex Wavelet Transform
  • Video sensor network for real-time traffic monitoring and surveillance
  • Error-Resilient H.264/AVC Video Transmission Using Two-Way Decodable Variable Length Data Block
  • IRIS Recognition Using Neural Network
  • A Secure Iris Image Encryption Technique Using Bio-Chaotic Algorithm
  • Relative Radiometric Correction of Cloudy Multitemporal Satellite Imagery
  • Region Duplication Detection Using Image Feature Matching
  • Content Based Image Retrieval using Hierarchical and K-Means Clustering Techniques
  • A rapid 3D seed-filling algorithm based on scan slice
Year 2011
  • A Point Feature-based Cylindrical Image Mosaic Method
  • Image Mosaics Algorithm Based on Feature-Block Matching
  • Modeling and Formalization of Fuzzy Finite Automata for Detection of Irregular Fire Flames
  • Real-time Sign Language Recognition based on Neural Network Architecture
  • Improved Biometric Recognition and Identification of human IRIS patterns using Neural Networks.
  • A robust detection algorithm for copy-move forgery in digital images
  • An Optimal Data Hiding Scheme With Tree-Based Parity Check
  • A Robust and Fast Video Copy Detection System Using Content-Based Fingerprinting
  • Matching Forensic Sketches to Mug Shot Photos
  • Automated classification of discrete human thoughts using functional magnetic resonance imaging (fMRI)
  • Automatic Road Detection Using MCSC
  • Dental biometrics Human identification based on teeth
  • Detection of Parked Vehicles Using Spatiotemporal maps
  • Text From Corners a Novel Approach to Detect Text and Caption in Videos 
  • Automatic Segmentation of NewBorn Brain MRI using Mathematical Morphology
Year 2012
  • Artifacts Removal and Edge Detection of Digitally Compressed Images
  • Gender Recognition from Face Images with Local WLD Descriptor
  • Drowsiness Detection based on Eye Movement, Yawn Detection and Head Rotation
  • Index Codes for Multibiometric Pattern Retrival
  • A Bayesian Technique for Image Classifying Registration
  • A Joint Encryption Watermarking System for erifying the Reliability of Medical Images
  • Framelet-Based Blind Motion Deblurring From a Single Image
  • Image Segmentation using Fuzzy Rule Based
  • Index Codes for Multibiometric Pattern Retrieval
  • In-painting approach to repair cracked images
  • Multistage Image Clustering and Segmentation with Normalised Cuts
Year 2013
  • Image steganography in DWT domain using double-stegging with RSA encryption
  • Spine Image Fusion via Graph Cuts
  • Heterogeneous Face Recognition Using Kernel Prototype Similarities
  • 3D Face Recognition under Expressions,Occlusions, and Pose Variations
  • A Secure Image Steganography Based on RSA Algorithm and Hash-LSB Technique
  • Detection and Removal of Cracks in Digitized Paintings
  • Emotion recognition from geometric facial features using self-organizing map
  • Image Adaptive Enhancement Strategy Based on Neural Network
  • Cellular Automata for unsupervised remotely sensed data classification 
  • Computerized Detection of Lung Nodules by Meansof “Virtual Dual-Energy” Radiography 
  • Separable Reversible Data Hiding Using Rc4 Algorithm
  • Superpixel Classification Based Optic Disc and Optic Cup Segmentation for Glaucoma Screening
  • Video Object Tracking in the Compressed Domain Using Spatio-Temporal Markov Random Fields
  • Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems
Year 2014
  • Image Fusion Based On Wavelet Transform 
  • Localization of License Plate Number Using Dynamic Image Processing Techniques and Genetic Algorithms
  • A New Secure Image Transmission Technique via Secret-Fragment-Visible Mosaic Images by Nearly Reversible Color Transformations
  • Data Hiding in Encrypted H.264/AVC Video Streams by Codeword Substitution 
  • Detection of Lung Cancer using Sputum Image Segmentation 
  • An ultrasound image enhancement method using local gradient based fuzzy similarity
  • Content Based Image Retrieval Using Interactive Genetic Algorithm 
  • Satellite Image Fusion using Fast Discrete Curvelet Transforms
  • Activity Recognition in Egocentric Life-logging Videos
Year 2015
  • A Review on-Image Fusion using Wavelet Transform
  • Automatic Vehicle Number Plate Recognition for Vehicle Parking Management System
  • EMR-A Scalable Graph-based Ranking Model for Content-based Image Retrieval
  • Spontaneous Micro-expression Spotting via Geometric Deformation Modeling using Random Walk-ANN 
  • Multi-Frame Example-Based Super-Resolution Using Locally Directional Self-Similarity
  • A Robust and Reversible Watermarking Technique for Relational Data 
  • A Discrete Wavelet Transform a Steganographic Method for Transmitting Images 
  • Ancient Cuneiform Text Extraction Based on Automatic Wavelet Selection
Year 2016
  • A new intra prediction with adaptive template matching through finite state machine
  • Secure Image Transmission Based On Pixel Integration Technique
  • Multi image integration and Encryption Algorithm for security applications
  • Egocentric Activity Recognition with Multimodal Fisher Vector
  • Bitplane Image Coding With Parallel Coefficient Processing
  • Enhancing Sketch-Based Image Retrieval by Re-Ranking and Relevance Feedback
  • Representation Learning of Temporal Dynamics for Skeleton-Based Action Recognition
  • Robust Face Sketch Style Synthesis
     
 SIGNAL PROCESSING
  • Speech Emotion Recognition Based on HMM AND SVM-2005
  • Improving the intelligibility of dysarthric speech-2007
  • Content-Based Music Information Retrieval: Current Directions and Future Challenges-2008
  • An Overview of Text-Independent Speaker Recognition: from Features to Supervectors-2009
  • ECG Arrhythmia Classification with Support Vector Machines and Genetic Algorithm-2009
  • Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis-2009
  • Speech Enhancement Using Harmonic Emphasis and Adaptive Comb Filtering-2010
  • Implementing a Speech Recognition System Interface for Indian Languages-2010
  • Calibration of Confidence Measures in Speech Recognition-2011
  • Broad Acoustic Classification of Spoken Hindi Hybrid Paired Words using Artificial Neural Networks-2012
  • Design and Development of a Malayalam to English Translator-2012
  • Speech and Speaker Recognition System using Artificial Neural Networks and Hidden Markov Model-2012
  • Multiclass epileptic seizure classification using time- frequency analysis of EEG signals-2012 
  • Audio Watermarking Via EMD-2013 
  • Intelligibility enhancement of HMM generated speech in additive noise by modifying Mel cepstral coefficients to increase the glimpse proportion-2013
  • Audio Steganography using RSA Algorithm and Genetic based Substitution method to Enhance Security-2014
  • GA-based Approach with Reduced RSA Encryption Security for Audio Steganography-2014
NETWORKING
  • DUCHA: A New Dual-channel MAC Protocol for Multihop Ad Hoc Networks-2006
  • Adaptive Routing in Dynamic Ad Hoc Networks-2008
  • Cooperative MIMO-Beamforming For Multiuser Relay Networks-2009
  • A Medium Access Control Scheme for TDD-CDMA Cellular Networks with Two-Hop Relay Architecture-2009
  • Single-Link Failure Detection in All-Optical Networks Using Monitoring Cycles and Paths-2009
  • A Matrix-Based Pairwise Key Establishment Scheme for Wireless Mesh Networks Using Pre Deployment Knowledge-2013 
  • A Clustering Routing Protocol for Energy Balance of Wireless Sensor Network based on Simulated Annealing and Genetic Algorithm-2014

The above listed topics are just for reference. If you have any new Ideas/Papers send to us at info@verilogcourseteam.com or Call +91 98942 20795.

Saturday

VARIANCE-REDUCED PARTIAL PARALLEL INTERFERENCE CANCELLATION FOR MC-CDMA UPLINK SYSTEMS

MULTICARRIER code division multiple access (MCCDMA) is one of the promising techniques for fourth generation wireless mobile communication systems. MCCDMA has several advantages, such as efficient spectrum utilization and immunity to multipath impairment. One major drawback associated with MC-CDMA is that multiuser detection is often necessary to overcome the multiple access interference (MAI) problem in uplink systems. Many multiuser detection approaches have been proposed in the literature .Among them, multistage parallel interference cancellation (PIC) has received great attention because of its low complexity and low processing latency, but it fails to guarantee performance improvement with more interference cancellation (IC) stages in moderate to high system load environments. To alleviate this problem, Divsalar et al. proposed the partial PIC (PPIC) detector, which first estimates MAI and then partially cancels it from the received signal on a stage-by-stage basis. Moshavi also indicated in that linearly combining soft tentative decisions of each IC stage can reduce the variance of the signal estimate, which will generate more reliable MAI estimates. As revealed in, a bit estimator that linearly combines the soft decisions from previous stages at a given stage for interference cancellation is inherently used by the PPIC approach. Therefore, the PPIC approach outperforms the PIC approach. Because the PPIC detector introduces weighting factors (WFs) to each IC stage, the performance depends highly on the choice of them. For good performance, two optimal WF (OWF) selection schemes based on analyzing the bit-error-rate (BER) were proposed for CDMA systems. However, the complexity of BER analysis increases greatly with the number of IC stages, and these approaches generally are not suitable for applications with more than two IC stages.

In this project, an improved version of PPIC, called variance-reduced PPIC (VRPPIC),for C-CDMA uplink systems. First,the main PPIC operations, where (the number of active users) multiplications of the original PPIC scheme are replaced with additions for each IC stage.Then we derive VRPPIC based on this simplified PPIC, where a new bit estimator is used for linearly combining soft tentative decisions from PPIC to reduce the conditional variance of the final signal estimate. In addition, an OWF selection algorithm for VRPPIC based on minimizing a conditional variance function of the final signal estimate. With the monotonically increasing property of the conditional variance function, it is shown that the OWFs for all IC stages are equal and can be approximately expressed as a linear function of the number of active users. Computer simulation results show that the proposed VRPPIC using the derived OWFs significantly improves the system performance.

VIDEO DEMO