@conference {
	title = {Constructing Optimal Wavelet Basis for Image Compression},
	author = {Zhuang, Yan., Baras, John S.},
	year = {1996},
	month = {05/1996},
	abstract = {We study the problem of choosing an image based optimal wavelet basis with compact support for image data compression and provide a general algorithm for computing the optimal wavelet basis. We parameterize the mother wavelet and scaling function of wavelet systems through a set of real coefficients of the relevant quadrature mirror filter (QMF) banks. We further introduce decomposition entropy as an information measure to describe the distance between a given digital image and its projection into the subspace spanned by the wavelet basis. The optimal basis for the given image is obtained through minimizing this information measure. The resulting subspace is used for image analysis and synthesis. Experiments show improved compression ratios due to the application of the optimal wavelet basis and demonstrate the potential applications of our methodology in image compression. This method is also useful for constructing efficient wavelet-based image coding systems.},
	address = {Atlanta, Georgia},
	booktitle = {IEEE (ICASSP) Conference on Acoustics, Speech, and Signal Processing},
	pages = {pp. 2351-2354}
}
@conference {
	title = {Image Compression Using Optimal Wavelet Basis},
	author = {Zhuang, Yan., Baras, John S.},
	year = {1995},
	month = {04/1995},
	abstract = {We study the problem of choosing an image based optimal wavelet basis with compact support for image data Compression and provide a general algorithm for computing the optimal wavelet basis. We parameterize the mother wavelet and the scaling function of wavelet systems through a set of real coefficients of the relevant quadrature mirror filter (QMF) banks. We further introduce the concept of decomposition entropy as an information measure to describe the distance between a given digital image and its projection into the subspace spanned by the wavelet basis. The optimal basis for the given image is obtained through minimizing this information measure. The resulting subspace is used for image analysis and Synthesis. A gradient based Optimization algorithm is developed for computing the image based optimal wavelet basis. Experiments show improved compression ratios due to the application of the Optimal wavelet basis and demonstrate the potential applications of Our methodology in image Compression. This method is also useful for constructing efficient wavelet-based image coding systems.},
	address = {Orlando, FL},
	booktitle = {The SPIE 1995 International Symposium on Aerospace/ Defense Sensing and Dual-Use Photonics},
	pages = {pp 131-140}
}
@conference {
	title = {Optimal Wavelet Basis Selection for Signal Representation},
	author = {Zhuang, Yan., Baras, John S.},
	year = {1994},
	month = {04/1994},
	abstract = {We study the problem of choosing an optimal wavelet basis with compact support for signal representation and provide a general algorithm for computing the optimal wavelet basis. We first briefly review the multiresolution property of wavelet decompositions and the conditions for generating an Orthonormal basis of compactly supported discrete wavelets in terms of properties of quadrature mirror filter (QMF) banks. We then parameterize the mother wavelet and scaling function of wavelet systems through a set of real coefficients. We further introduce the concept of decomposition entropy as an information measure to describe the distance between a given signal and its projection onto the subspace spanned by the wavelet basis in which the signal is to be reconstructed. The optimal basis for the given signal is obtained through minimizing this information measure. We have obtained explicitly the sensitivity of dilations and shifts of the mother wavelet with respect to the coefficient set. A systematic approach is developed in this paper to derive the information gradient with respect to the parameter set from a given square integrable signal and an initial discrete basis of wavelets. The existence of the optimal basis for the wavelets has been proven in this paper. A gradient based Optimization algorithm is developed for computing the optimal wavelet basis.},
	address = {Orlando, FL},
	booktitle = {The SPIE International Symposium on Intelligent Information Systems},
	pages = {pp. 200-211}
}
@conference {
	title = {Shape Optimization of Distributed Sensors and Actuators for Smart Structure Control},
	author = {Zhuang, Yan., Baras, John S.},
	year = {1994},
	month = {02/1994},
	abstract = {We describe a design technique for optimal control in active structural vibration damping using smart materials. The vibration of a cantilever beam is stabilized by feedback the weighted integration of vibration velocity in the closed loop system through the application of distributed sensors and actuators made of smart materials. We model the beam by the Timoshenko beam model embedded with the distributed sensors and actuators to account for the shear and inertial effects on the structures. We propose an algorithm to find the optimal placement of the actuators and sensors so as to maximize the damping effect. An objective functional is defined based on the vibration energy of the system. The optimal shapes of the sensor and actuator are determined through minimizing the energy functional of the beam over the admissible shape function space subject to certain constraints. This~approach can be generalized to cases of plate damping and active control of more complicated smart structures as well.},
	address = {Orlando, FL},
	booktitle = {The SPIE: 1994 North American Conference on Smart Structures and Materials},
	pages = {pp. 381-388}
}
@conference {
	title = {Optimal Design of Distributed Sensors and Actuators Made of Smart Materials for Active Vibration Control},
	author = {Zhuang, Yan., Baras, John S.},
	year = {1993},
	month = {05/1993},
	abstract = {We describe a design technique for optimal control in active structural vibration damping using smart materials. The vibration of a cantilever beam is stabilized by using distributed sensors and actuators. We model the beam by the Timoshenko beam model together with the distributed sensors and actuators. A control law using the weighted integration of vibration velocity is incorporated in the closed loop system. We propose a method to find the optimal layout design of the smart material so as to maximize the damping effect. An objective functional is defined based on the vibration energy of the system. The optimal shapes of the sensor and actuator are determined through minimizing the energy functional of the beam over the admissible shape function space subject to certain geometric constraints. An algorithm has been developed to determine the optimal sensor and actuator layout. This method can be generalized to the plate damping problem and more complicated structures as well.},
	address = {Thousand Oaks, CA},
	booktitle = {The 1993 IEEE Regional Conference on Aerospace Control Systems},
	pages = {pp. 65-69},
	organization = { Rockwell Science Center}
}
@conference {
	title = {Distributed Control of a Timoshenko Beam},
	author = {Zhuang, Yan., Baras, John S.},
	year = {1992},
	month = {11/1992},
	abstract = {We consider a flexible beam clamped to a rigid base on one end with the other end free. In order to stabilize the beam vibration, we introduce active damping into the beam with feedback control using distributed actuators and sensors. We apply Tim Oshenko beam theory to model the substructure. Unlike the familiar Euler-Bernoulli beam model, the shear effect and the rotational inertia are included in the modeling of elastic deformation to obtain a more precise beam model. The piezoelectric~theory is briefly reviewed. The piezoelectric ceramic material (PZT) is used to build the distributed actuator. The distributed sensor is made of piezoelectric polymer polyvinylidene fluoride (PVDF). The sensor and actuator are layers which are attached directly to both sides of the beam. Based on the constitutive properties and layer geometry, the models for sensor and actuator are developed. We then embed the static actuator and sensor models into the beam substructure to form the model of the composite beam. We design the feedback controller by Lyapunov direct methods based on the energy functional of the system. It is proved that the derived controller can extract energy from the system and increase system damping. The resulting closed loop system is asymptotically stable. Since this method does not depend on model truncation, we further analyze the combined effect of the distributed controller on the relevant vibration modes. It is possible to suppress the selected modes by choosing the appropriate actuator layout. It is also shown that by properly installing the sensor and determining the sensor shape function,~we can further extract and manipulate the sensor signal for our control need.

~

~},
	address = {San Diego, CA},
	booktitle = {The Third International Conference on Adaptive Structures},
	pages = {pp. 216-227}
}
@conference {
	title = {Active Vibration Damping Using Smart Material},
	author = {Baras, John S., Zhuang, Yan.},
	year = {1992},
	month = {06/1992},
	abstract = {We consider the Modeling and active damping of an elastic beam using distributed actuators and sensors. The piezoelectric ceramic material (P7T) is used to build the actuator. The sensor is made of the piezoelectric polymer polyvinylidene fluoride (PVDF). These materials are glued on both side of the beam. For the simple clamped beam, the closed loop controller has been shown to be able to extract energy from the beam. The shape of the actuator and its influence on the closed loop system performance are discussed. It is shown that it is possible to suppress the selected mode by choosing the appropriate actuator layout. It is also shown that by properly installing the sensor and determine the sensor shape we can further extract and manipulate the sensor signal for our control need.},
	address = {Williamsburg, Virginia},
	booktitle = {Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems},
	pages = {pp. 1-14}
}
