Signal Analysis Research (SAR) Group - RNet - Ryerson University

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2004.05 Sub-Dictionary Selection Using Local Discriminant Bases Algorithm for Signal Classification K. Umapathy, S. Krishnan and A. Das 2003.09 Ultrasound Backscatter Signal Characterization and Classification Using Autoregressive Modeling and Machine Learning Algorithms N.R. Farnoud, M. Kolios and S. Krishnan 2003.07 Robust Audio Watermarking Using a Chirp Based Technique S. Erkucuk, S. Krishnan and M. Zeytinoglu 2003.07 Time-Frequency Filtering of Interferences in Spread Spectrum Communications S. Erkucuk and S. Krishnan 2003.05 A General Perceptual Tool for Evaluation of Audio Codecs K. Umapathy, S. Krishnan and G. Sinanian 2003.05 Non-Stationary Noise Cancellation in Infrared Wireless Receivers S. Krishnan, X. Fernando and H. Sun 2003.04 Adaptive Denoising at Infrared Wireless Receivers X. N. Fernando, S. Krishnan, H. Sun and K. Kazemi-Moud 2003.04 Audio Watermarking Using Time-Frequency Characteristics S. Esmaili, S. Krishnan and K. Raahemifar 2002.10 Time-Frequency Modeling and Classification of Pathological Voices K. Umapathy, S. Krishnan, V. Parsa and D. Jamieson 2002.08 Audio Signal Classification Using Time-Frequency Parameters K. Umapathy, S. Krishnan and S. Jimaa 2002.05 Detection of Linear Chirp and Non-Linear Chirp Interferences in a Spread Spectrum Signal by Using Hough-Radon Transform S. Thayilchira and S. Krishnan 2002.05 Discrimination of Pathological Voices Using an Adaptive Time- Frequency Approach K. Umapathy, S. Krishnan, V. Parsa and D. Jamieson 2002.05 Interference Excision in Spread Spectrum Communications Using Adaptive Positive Time-Frequency Distributions S. Erkucuk and S. Krishnan 2001.05 Fixed Block-Based Lossless Compression of Digital Mammograms M.Y. Al-Saiegh and S. Krishnan 113 - 116 117 – 120 121 – 124 125 – 128 129 – 132 133 – 137 138 – 146 147 – 151 152 - 153 154 - 157 158 159 - 162 163 164 - 169
2001.05 Instantaneous Mean Frequency Estimation Using Adaptive Time- Frequency Distributions S. Krishnan 2000.07 Sonification of Knee-joint Vibration Signals S. Krishnan, R.M. Rangayyan, G.D. Bell and C.B. Frank 1999.05 Denoising Knee Joint Vibration Signals Using Adaptive Time- Frequency Representations S. Krishnan and R.M. Rangayyan 1998.10 Comparative Analysis of the Performance of the Time-Frequency Distributions with Knee Joint Vibroarthrographic Signals R.M. Rangayyan and S. Krishnan 1998.10 Detection of Nonlinear Frequency-Modulated Components in the Time-Frequency Plane Using an Array of Accumulators S. Krishnan and R.M. Rangayyan 1997.10 Time-Frequency Signal Feature Extraction and Screening of Knee Joint Vibroarthrographic Signals Using the Matching Pursuit Method S. Krishnan, R.M. Rangayyan, G.D. Bell and C.B. Frank 1997.08 Detection of Chirp and Other Components in the Time-Frequency Plane Using the Hough and Radon Transform S. Krishnan and R.M. Rangayyan 1997.08 Spatial-Temporal Decorrelating Decision-Feedback Multiuser Detector for Synchronous Code-Division Multiple-Access Channels S. Krishnan and B.R. Petersen 1996.10 Screening of Knee Joint Vibroarthrographic Signals by Statistical Pattern Analysis of Dominant Poles S. Krishnan, R.M Rangayyan, G.D. Bell, C.B. Frank and K.O. Ladly 1996.05 Recursive Least-Squares Lattice-Based Adaptive Segmentation and Autoregressive Modeling of Knee Joint Vibroarthographic Signals S. Krishnan, R.M. Rangayyan, G.D. Bell, C.B. Frank and K.O. Ladly Other Refereed Conference Papers 170 – 175 176 – 179 180 – 185 186 - 189 190 - 193 194 – 197 198 - 201 202 - 207 208 – 209 210 - 213 214 - 215
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Acknowledgements This work of Ryers
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ing two consecutive keys. Another c
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Table 1. Experimental Results for F
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D as { gγ γ ∈ Γ, g = 1} = γ ,
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frequency parameters issued from th
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necessity of prediction, controllin
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4. Experimental Results The objecti
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This full text paper was peer revie
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This full text paper was peer revie
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Proceedings of the 2005 IEEE Engine
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the whole spectrum but on non-overl
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Identification Rate 1 0.9 0.8 0.7 0
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signals. On some occasions, when us
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For our first test, we recorded two
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Frequency bands F4 F3 F2 F1 ME5 s1
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as F1, F2, F3 and F4 as shown in Fi
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Figure. 1. Motion Vector magnitudes
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All the above descriptor were quant
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2. METHODOLOGY 2.1. Local Discrimin
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. each group, the posterior probabi
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A NOVEL ROBUST IMAGE WATERMARKING U
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where n is the distortion component
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A Novel Way of Lossless Compression
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111. IMPLEMENTATION As we have pres
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CONTENT BASED AUDIO CLASSIFICATION
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Entropy 4.5 4 3.5 3 2.5 2 1.5 1 0.5
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MODIFIED LOCAL DISCRIMINANT BASES A
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Tree Decomposition (0,0) (1,0) (1,1
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RADIO OVER MULTIMODE FIBER FOR WIRE
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3. COMPARISON OF MULTIMODE FIBER AN
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SUB-DICTIONARY SELECTION USING LOCA
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Proceedings of the 25h Annual Inter
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estimated noise generated as the ou
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ROBUST AUDIO WATERMARKING USING A C
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where 0 is the angle of the ray pat
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TIME-FREQUENCY FILTERING OF INTERFE
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3. INTERFERENCE DETECTION. nouen AN
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A GENERAL PERCEPTUAL TOOL FOR EVALU
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Fig. 2. Snapshot of the GUI used fo
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Non-Stationary Noise Cancellation i
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signal and noise spectra overlap, f
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Fig. 4: Output of the Comb filter.
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Indoor infrared transmission suffer
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The inverse wavelet transform is de
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The simulations has been done using
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Figure 6: The original Gaussian noi
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147 Authorized licensed use limited
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Figure 2: Block diagram of the FBB
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Figure 4: Benign mammogram before F
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. Table 1: Compression ratios of be
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Most Cohen’s class TFD derived fr
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the desired frequency marginal m(w)
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constructing an adaptive TFD and ex
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Proceedings of the 22"d Annual EMBS
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are: Proceedings of the 22"d Annual
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may be written as M-1 = (z,grn)gm,
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using the denoised signals. As an i
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signals are: 1) model-based TFD, 2)
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compared to that in the MP dictiona
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fied. In addition to being positive
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08 [3] S. Peleg and B. Friedlander.
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Proceedings - 19th International Co
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Proceedings - 19th International Co
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the x and y axes correspond to the
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Fig. 5. Results with synthetic sign
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the users and is explained in next
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18th Annual International Conferenc
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quisition board and Lab Windows (Na
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Table 1: Comparison of different cl
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K. Umapathy and S. Krishnan, Low bi
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Signal Analysis Research (SAR) Group - RNet - Ryerson University

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