Various algorithms have been studied for analysis, modification and synthesis of signals and images. Application domains include acoustics, image processing and  biological data. 

 

Independent Component Analysis

A transform designed to provide maximum independence among its output is an Independent Component Analyzer (ICA). We have contributed with various algorithms and structures to this paradigm.  

 

• Budillon A., Palmieri F. and Varriale R., "A Hybrid Method for Signal De-noising via Independent Component Analysis," Proc. of International Workshop on Independent Component Analysis (ICA'2000), Helsinki, Finland, June 2000.
• Palmieri F., Budillon, F. "Unsupervised Rank-deficient Density Estimation via Multi-Class Independent Component Analysis," Proc. of International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, July 2000.
• F. Palmieri, D. Mattera and A. Budillon, "Multi-Layer Independent Component Analysis (MLICA)," Proceedings of First Internation Workshop on Independent Component Analysis and Signal Separation, Aussois, France, pp. 93-97, Jan 1999.
• F. Palmieri, A. Budillon, D. Mattera, "Independent Component Analysis for Mixture Densities," Proceedings of European Symposium on Artificial Neural Networks, ESANN'99, Bruge, Belgium, April 1999.
• F. Palmieri, A. Budillon, M. Calabrese and D. Mattera, "Searching for a Binary Factorial Code Using the ICA Framework," Neurocomputing, Vol 22, pp. 131-144, 1998.

 

2D Phase Unwrapping

In retote sensing applications, such as Synthetic Aperture Radar (SAR),  a crucial role is played by algorithms that have to unfold the phase (phase unwrapping). We have proposes  two approaches, one  based on a discretization of Green's operators, and one on genetic algorithms.  

 

 

• S. Marano, F. Palmieri, and G. Franceschetti, "Discrete Green's Methods and their application to two-dimensional phase unwrapping," The Journal of Optical Society of America, Vol. 19, N. 7, July 2002.
• A. Collaro, G. Franceschetti, F. Palmieri and M. S. Ferreiro, "Phase Unwrapping via Genetic Algorithms," Journal of the Optical Society of America, Part A, Vol. 15, N. 2, pp. 407-418, Feb. 1998.

 

Speech Prosody Modification

The pitch contour in speech is what makes the signal sound expressive. Manipulation of this intonation in speech processing, or sythesis, requires careful algorithm design to preserve, or produce, natural soundness. We have explored Fujisaki's model in altering the prosody of natural speech signals.      

 

• P. Salvo Rossi, P. Falco, A. Budillon, D. Mattera and F. Palmieri, "Prosody modification and Fujisaki's model: Preserving natural soundness," Proceedings of European Signal Processing Conference, EUSIPCO 2004, Vienna, Sept 2004, pp. 1019-1022.
• P. Salvo Rossi, F. Palmieri, F. Cutugno, "Inversion of F0 Model for Natural-Sound Speech Synthesis," Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP-2003), Hong Kong, April 2003, Vol. I, pp. 520-523.
• Lettieri N., Cutugno F., Palmieri F., ''Algoritmi per la modifica per via sintetica della curva intonativa in parlato naturale," Atti del XXVIII Convegno Nazionale dell'Associazione Italiana di Acustica, Trani, Bari, 10-13 giugno 2000.

 

Sampling Theorem

A sampling theorem for polynomial intepolation has been proposed for signals and functions that belong to the exponential family. The regions of converge of the piecewise interpolations, for both, one-sided, and two-sided interpolation, genaralize the well-known Nyquist criterion.  

 

• F. Palmieri, "Sampling Theorem for Polynomial Interpolation," IEEE Trans. on Acoustics Speech and Signal Processing, Vol. ASSP-34, pp. 846-857, August 1986.

 

Order Statistic Filters

Order statistic filter are based on linear combinations of ranked samples within each observation window. A well-known case is the median filter. We have generalized the class and introduced the so-called Ll-filters.Various algorithms for characterization and design of these filters have been proposed with applications to one- and two-dimensional signals.    

 

• F. Palmieri and A. Shah, "Application of the Adaptive Recursive Order Statistic Filter to ADPCM," Tech. Rep. TR-92-11, Dept of Electrical and Systems Eng., The University of Connecticut, Storrs, CT 06269-3157, June 1992.
• R. E. Croteau, F. Palmieri, "Adaptive Channel Equalization Using Generalized Order Statistic Filters," Tech. Rep. TR-92-10, Dept of Electrical and Systems Eng., The University of Connecticut, Storrs, CT 06269-3157, , June. 1992.
• F. Palmieri and R. E. Croteau, "Adaptive Channel Equalization Using Generalized Order Statistic Filters," Proceedings of 1991 IEEE Int. Conference on Acoustics Speech and Signal Processing, Toronto, Canada, pp. 1933-1936, May 1991.
• F. Palmieri and R. E. Croteau, "Image Restoration Based on Perception-Related Cost Functions," (invited paper) Proceedings of SPIE/SPSE Symposium on Electronic Imaging, Science and Technology, San Jose, Ca, Volume on Nonlinear Image Processing, pp. 24-35, Feb 1991.
• F. Palmieri, R. E. Croteau, "On the Use of Ll-Filters for Adaptive Channel Equalization," Proceedings of the IEEE Third Biennal Acoustics, Speech and Signal Processing Mini Conference, Weston, MA, pp. S7.1-2, April 1991.
• F. Palmieri and C. G. Boncelet Jr., "Frequency Analysis and Synthesis of a Class of Nonlinear Filters," IEEE Trans. on Acoustics Speech and Signal Processing, Vol. ASSP-38, N. 8, pp. 1363-1372, Aug 1990.
• F. Palmieri and C. G. Boncelet Jr., "Ll-filters, A New Class of Order Statistic Filters," IEEE Trans. on Acoustics Speech and Signal Processing, Vol. ASSP-37, N. 5, pp. 691-701, May 1989.
• F. Palmieri, "A Backpropagation Algorithm for Multilayer Hybrid Order Statistic Filters," Proceedings of the 1989 IEEE International Conference on Acoustics Speech and Signal Processing, Glasgow, Scotland, UK, pp. 1179-1182, May 1989.
• F. Palmieri and C. G. Boncelet Jr., "A Class of Adaptive Nonlinear Filters," Proceedings of IEEE Int. Conference on Acoustics Speech and Signal Processing, New York City, pp. 1483-86, April 1988.
• F. Palmieri and C. G. Boncelet Jr., "Design of Order Statistic Filters I: L-Filters," University of Delaware, Electrical Engineering Department, Tech. Rep. 88-4-2, April 1988.
• F. Palmieri and C. G. Boncelet Jr., "Design of Order Statistic Filters II: Ll-Filters," University of Delaware, Department of Electrical Engineering, Tech. Rep. 88-4-3, April 1988.
• F. Palmieri and C. G. Boncelet Jr., "Design of Order Statistic Filters with Given Spectral Behavior," Proceedings of the Conference on Information Sciences and Systems, The Johns Hopkins University, Baltimore, MD, March 1987.
• F. Palmieri, "Nonlinear Filtering for Robust Signal Processing," PhD Thesis in Electrical Engineering, University of Delaware, August 1987.
• F. Palmieri and C. G. Boncelet Jr., "Optimal MSE Linear Combination of Order Statistics for Restoration of Markov Processes," Proceedings of the Twentieth Annual Conference on Information Sciences and Systems, Princeton, NJ, March 1986.
• F. Palmieri and C. G. Boncelet Jr., "Ll-Filters," (Short Paper), Proceedings of the Twenty-Fourth Allerton Conference on Communications Control and Computing, Urbana, IL, October 1986.

 

Event Prediction on Geomagnetic Sequences

Event detection based on innovations on RLS-based predictors, are applied to geomagnetic time series measured in the proximity of erupting vulcanos.   

 

• M. Fedi, M. La Manna, F. Palmieri, ''Non stationary Analysis of Geomagnetic Time Sequences from Mt. Etna and North Palm Springs Earthquake," Journal of Geophysical Research, Vol. 108, N. B10, 2003, pp. 7:1-7:15.

 

Pattern Recognition on Mammograms

A pattern classification technique has been proposed for classifying tumor shapes from mammograms. The technique is based on the classical scheme of a parameter extractor followed by a classifier. Shape parameters are extracted for  a 3-class decision.   

 

• J. Kilday, F. Palmieri, M. D. Fox, "Classifying Mammographic Lesions Using Computerized Image Analysis of Tumor Shape," IEEE Trans. on Medical Imaging, Vol. 12, N. 4, pp. 664-669, Dec 1993.
• J. Kilday, F. Palmieri, M. Fox, "Linear Discriminant-Based Mammographic Tumor Classification Using Shape Descriptors," Proceedings of the 12th Annual IEEE Int. Conference of Engineering in Medicine and Biology Society, Philadephia, PA, Nov. 1990 (Best Student Paper Award).

 

Location of Partial Discharge in Cables

Faults in underground high-voltage cables, can be detected using measurements on the reflected signals produced by partial discharges induced during testing. We have proposed signal processing algorithms for accurate location estimation.    

 

• M. S. Mashikian, F. Palmieri, R. Bansal and R. B. Northrop, "Location of Partial Discharges in Shielded Cables in the Presence of High Noise," IEEE Trans. on Electrical Insulation, Vol. 27, N. 1, pp. 37-43, Feb. 1992.
• Z. Du, F. Palmieri, M. Mashikian, "A Partial Discharge Propagation Model and Location Estimate," Proc. of Int. Conference on DSP Applications and Technology, Cambridge, MA, Nov. 1992.

 

Window Functions

In designing digital filters and in spectral estimation, window functions are used to control the effects of finite length observations. We have proposed a class of window functions based on piecewice polynomial that can be designed for smoothness control.     

 

• F. Palmieri and L. P. Bolgiano Jr., "Window Functions Obtained from B-Splines," Proceedings of the IEEE Int. Conference on Acoustics Speech and Signal Processing, Tampa, FL, pp. 85-88, April 1985.
• F. Palmieri, "Polynomial Window Functions," Final Thesis, Master's in Applied Sciences (Electrical Engineering), University of Delaware, June 1985.

 

Reconstruction from Projections

Internal structures of solid objets can we recostructed from projections gathered externally through x-rays (CAT scan). A priori knowledge  on the objects composing the unknown structures can help in obtaining smoother recostructions.  

 

• I. Abdou and F. Palmieri, "On Using A Priori Knowledge in Reconstruction from Projections," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, pp. 390-392, June 1985.

 

Speaker Recognition

Speech can be processed to recognize the speaker. We have experimented with LPC - Linear Prediction Coefficients  for reliable speaker identification.  

 

• F. Palmieri and M. Longo, "Speaker Identification Using Averaged Prediction Coefficients," Proceedings of the Fourth FASE Symposium}, Venice, Italy, April 1981.
• F. Palmieri and M. Longo, "Un Esperimento di Riconoscimento Automatico del Parlatore Basato sull'Analisi LPC," Rapp. Tec. 02-81, Laboratorio di Comunicazioni Elettriche, Istituto di Elettrotecnica, Universita' di Napoli, Marzo 1981.
• F. Palmieri, "Un Esperimento per Valutare l'Efficacia dei Parametri LPC nel Riconoscimento Automatico del Parlatore," Tesi di Laurea in Ingegneria Elettronica, Universita' degli Studi di Napoli, Ottobre 1980.

 

Filter Design 

Digital filters can be designed and implemented in various architecture. We have proposed an architecture for non-causal filters and proposed a technique for sparse filter design.  

 

• D. Mattera, F. Palmieri, "Non Causal Filters: Possible Implementations and their Complexity," Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP-2003), Hong Kong, April 2003, Vol. VI, pp. 365-368.
• Mattera D., F. Palmieri and S. Haykin, "Efficient sparse FIR filter design." Proceeding of IEEE Int. Conf. on Acoustics Speech and Signal Processing, ICASSP-2002, Orlando, FL, May 14-17, 2002, Vol. II, pp. 1537-1540.

 

Signal Compression

We have proposed a technique that induces sparsity on the solution of linear systems in signal compression. 

 

• Mattera D. and F. Palmieri, "A comparison of signal compression methods by sparse solutions of linear systems," Proc. of 2002 int. Workshop on Neural Nets, WIRN-2002, May 30-June 1, 2002, Vietri s.m., Salerno, Italy, Springer Verlag.

 

Analog-to-Digital Conversion

We have designed a software interface for efficient analog-to-digital conversion based on a multiplex. 

 

• F. Palmieri, L. Vetrano and M. Longo, "Sistema di Acquisizione Dati su Calcolatore HP-1000," Rapp. Tech. 01-82, Istituto Onde Elettromagnetiche, Istituto Universitario Navale di Napoli, Aprile 1982.