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  • ESE 511: Modern Optics and Image Understanding

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): ESE 310, graduate standing, or permission of the instructor. The goal of this course is to provide a unified approach to modern optics, image formation, analysis, and understanding that form the theoretical basis for advanced imaging systems in use today in science, medicine and technology. The emphasis is on imaging systems that employ electromagnetic energy but the principles covered can be extended to systems employing other forms of radiant energy such as acoustical.
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  • ESE 514: Physics of Materials I

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): Undergraduate Physics and Math through modern physics and differential equations. Failures of classical physics and the historical basis for quantum theory. Postulates of wave mechanics; uncertainty principle, wave packets and wave-particle duality. Shrodinger equation and operators; eigenvalue problems in 1 and 3 dimensions (barriers, wells, hydrogen atom). Mathematical equivalence to problems in optics. Perturbation theory; scattering of particles and light. Free electron theory of metals; Drude and Sommerfeld models, dispersion relations and optical properties of solids. Extensive use of computer-aided self-study will be made.
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  • ESE 515: Physics of Materials-II

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): MSE 570/ESE 514 or equivalent. Failures of free electron theory. Crystals and the reciprocal lattice; wave propagation in periodic media; Bloch's theorem. One-electron band structure models: nearly free electrons, tight binding. Semiclassical dynamics and transport. Cohesive energy, lattice dynamics and phonons. Dielectric properties of insulators. Homogeneous semiconductors and p-n junctions. Experimental probes of solid state phenomena: photo emission, energy loss spectroscopy, neutron scattering. As time permits, special topics selected from the following: correlation effects, semiconductor alloys and heterostructures, amorphous semiconductors, electroactive polymers.
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  • ESE 517: Optical Imaging

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): ESE 310 and 325 or equivalent. A modern introduction to the physical principles of optical imaging with biomedical applications. Propagation and interference of electromagnetic waves. Geometrical optics and the eikonal. Plane-wave expansions, diffraction and the Rayleigh criterion. Scattering theory and the Born approximation. Introduction to inverse problems. Multiple scattering and radiative transport. Diffusion approximation and physical optics of diffusing waves. Imaging in turbid media. Introduction to coherence theory and coherence imaging. Applications will be chosen from the recent literature in biomedical optics.
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  • ESE 521: Semiconductor Device Physics and Technology

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): ESE 218 or PHYS 240 or MSE 222 or equivalent, or by permission of the instructor. Free electron theory and density states, band theory of electronic conduction; review of semiconductor fundamentals and operation p-n homojunction; multijunction and interface devices; high-field and hot-electron devices; growth and technology of heterostructures, quantum wells and related quantum phenomena, high-frequency and high speed devices; LEDs and semiconductor lasers.
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  • ESE 522: Process Management in Manufacturing

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): OPIM 621, OPIM 631, and OPIM 632 or equivalent. This course builds on OPIM 631 and OPIM 632 in developing the foundations of process management, with applications to manufacturing and supply chain coordination and integration. This course begins with a treatment of the foundations of process management, including quality (e.g. 6-sigma systems) and time (e.g., cycle time) as building blocks for the sucessful integration of plant operations with vertical and horizontal market structures. On the e-manufacturing side, the course consideres recent advances in enterprise-wide planning (ERP)systems, supplier management and contract manufacturing. Industry case studies highlight contrasting approaches to the integration of manufacturing operations and risk management with e-Logistics and e-Procurement providers and exchanges. The course is recommended for those interested in consulting or operations careers, and those wishing to understand the role of manufacturing as a general foundation for economics value creation.
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  • ESE 525: Nanoscale Science and Engineering

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): ESE 218 or PHYS 240 or MSE 222 or equivalent, or by permission. Overview of existing device and manufacturing technologies in microelectronics, optoelectronics, magnetic storage, Microsystems, and biotechnology. Overview of near- and long-term challenges facing those fields. Near- and long- term prospects of nanoscience and related technologies for the evolutionary sustension of current approaches, and for the development of revolutionary designs and applications.
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  • ESE 529: RF MEMS and NEMS

    3.00 Credits
    University of Pennsylvania

    Introduction to RF MEMS and NEMS technologies. Need for RF MEMS and NEMS components in wireless communications. Review of micromachining techniques and MEMS and NEMS fabrication approaches. Actuation methods in MEMS and NEMS, MEMS and NEMS design and modeling. Examples of RF MEMS components from industry and academia. Case studies: micro and nano switches, tunable capacitors, inductors, micro and nano resonators, filters, oscillators and micromachined antennas.
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  • ESE 530: Elements of Probability Theory and Random Processes

    3.00 Credits
    University of Pennsylvania

    Prerequisite(s): A solid foundation in undergraduate probability at the level of STAT 430 or ESE 301 at Penn. Students are expected to have a sound calculus background as covered in the first two years of a typcial undergraduate engineering curriculum. Undergraduates are warned that the course is very mathematical in nature with an emphasis on rigour; upperclassmen who wish to take the course will need to see the instructor for permission to register. This rapidly moving course provides a formal framework for the development of fundamental ideas in probability theory. This course is a prerequisite for subsequent courses in communication theory and telecommunications such as ESE 576 and TCOM 501. The course is also suitable for students seeking a rigourous and broad graduate-level exposure to probabalistic ideas and principles with applications in diverse settings. Topics covered are taken from: discrete and continuous probability spaces; combinatorial probabilities; conditional probability and indepence; Bayes rules and the theorem of total probability; the inclusion-exclusion principle, Bonferroni's inequalities, the Poisson paradigm, probability sieves, and the Lovascz local lemma; arithmetic and lattice distributions; the central term and the tails of the binomial, Poisson approximation; densities in one and more dimensions; characterizations of the uniform, exponential and normal densities; probability spaces, random variables and distribution functions; transformations, random number generation; independent random variables, Borel's normal law; measures of central tendency---mean, median, mode, mathematical expectation; the monotone convergence theorem and its applications; additivity and monotonicity of expectations; moments; the inequalities of Markov, Chebyshev, Chernoff, and Talagrand; concentration phenomena and applications; limit theorems, the weak and strong laws; generating functions, recurrent events, Blackwell's theorem; characteristic functions, the central limit theorem.
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  • ESE 531: Digital Signal Processing

    3.00 Credits
    University of Pennsylvania

    This course covers the fundamentals of real-time processing of discrete-time signals and digital systems. Specific topics covered are: review of signals and linear system representations; convolution and discrete Fourier transforms; Z-transforms; frequency response of lienar discrete-time systems; sampling and analog/digital conversion; finite and infinite impulse response filters; digital filter design; fast Fourier transfers and applications; adaptive filtering algorithms; wavelet transforms. Projects requiring implementation of specific digital signal processing algorithms will also be assigned.
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