Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Effect of fourier domain quantization on matched filtering

It is shown that the use of a coarsely quantized binary digital hologram as a matched filter on an optical computer does not degrade signal-to-noise ratio (SNR) appreciably.

Molecular Tuning of Rhodopsins for High Visual Sensitivity in Different Light Environments : Variation in Absorbance Spectrum and Opsin Sequence within and between Species

Visual pigments of different animal species must have evolved at some stage to match the prevailing light environments, since all visual functions depend on their ability to absorb available photons and transduce the event into a reliable neural signal. There is a large literature on correlation between the light environment and spectral sensitivity between different fish species. However, little work has been done on evolutionary adaptation between separated populations within species. More generally, little is known about the rate of evolutionary adaptation to changing spectral environments. The objective of this thesis is to illuminate the constraints under which the evolutionary tuning of visual pigments works as evident in: scope, tempo, available molecular routes, and signal/noise trade-offs. Aquatic environments offer Nature s own laboratories for research on visual pigment properties, as naturally occurring light environments offer an enormous range of variation in both spectral composition and intensity. The present thesis focuses on the visual pigments that serve dim-light vision in two groups of model species, teleost fishes and mysid crustaceans. The geographical emphasis is in the brackish Baltic Sea area with its well-known postglacial isolation history and its aquatic fauna of both marine and fresh-water origin. The absorbance spectrum of the (single) dim-light visual pigment were recorded by microspectrophotometry (MSP) in single rods of 26 fish species and single rhabdoms of 8 opossum shrimp populations of the genus Mysis inhabiting marine, brackish or freshwater environments. Additionally, spectral sensitivity was determined from six Mysis populations by electroretinogram (ERG) recording. The rod opsin gene was sequenced in individuals of four allopatric populations of the sand goby (Pomatoschistus minutus). Rod opsins of two other goby species were investigated as outgroups for comparison. Rod absorbance spectra of the Baltic subspecies or populations of the primarily marine species herring (Clupea harengus membras), sand goby (P. minutus), and flounder (Platichthys flesus) were long-wavelength-shifted compared to their marine populations. The spectral shifts are consistent with adaptation for improved quantum catch (QC) as well as improved signal-to-noise ratio (SNR) of vision in the Baltic light environment. Since the chromophore of the pigment was pure A1 in all cases, this has apparently been achieved by evolutionary tuning of the opsin visual pigment. By contrast, no opsin-based differences were evident between lake and sea populations of species of fresh-water origin, which can tune their pigment by varying chromophore ratios. A more detailed analysis of differences in absorbance spectra and opsin sequence between and within populations was conducted using the sand goby as model species. Four allopatric populations from the Baltic Sea (B), Swedish west coast (S), English Channel (E), and Adriatic Sea (A) were examined. Rod absorbance spectra, characterized by the wavelength of maximum absorbance (λmax), differed between populations and correlated with differences in the spectral light transmission of the respective water bodies. The greatest λmax shift as well as the greatest opsin sequence difference was between the Baltic and the Adriatic populations. The significant within-population variation of the Baltic λmax values (506-511 nm) was analyzed on the level of individuals and was shown to correlate well with opsin sequence substitutions. The sequences of individuals with λmax at shorter wavelengths were identical to that of the Swedish population, whereas those with λmax at longer wavelengths additionally had substitution F261F/Y in the sixth transmembrane helix of the protein. This substitution (Y261) was also present in the Baltic common gobies and is known to redshift spectra. The tuning mechanism of the long-wavelength type Baltic sand gobies is assumed to be the co-expression of F261 and Y261 in all rods to produce ≈ 5 nm redshift. The polymorphism of the Baltic sand goby population possibly indicates ambiguous selection pressures in the Baltic Sea. The visual pigments of all lake populations of the opossum shrimp (Mysis relicta) were red-shifted by 25 nm compared with all Baltic Sea populations. This is calculated to confer a significant advantage in both QC and SNR in many humus-rich lakes with reddish water. Since only A2 chromophore was present, the differences obviously reflect evolutionary tuning of the visual protein, the opsin. The changes have occurred within the ca. 9000 years that the lakes have been isolated from the Sea after the most recent glaciation. At present, it seems that the mechanism explaining the spectral differences between lake and sea populations is not an amino acid substitution at any other conventional tuning site, but the mechanism is yet to be found.

ANC schemes for the enhancement of EEG signals in the presence of EOG artifacts

One of the most important applications of adaptive systems is in noise cancellation using adaptive filters. Ln this paper, we propose adaptive noise cancellation schemes for the enhancement of EEG signals in the presence of EOG artifacts. The effect of two reference inputs is studied on simulated as well as recorded EEG signals and it is found that one reference input is enough to get sufficient minimization of EOG artifacts. This has been verified through correlation analysis also. We use signal to noise ratio and linear prediction spectra, along with time plots, for comparing the performance of the proposed schemes for minimizing EOG artifacts from contaminated EEG signals. Results show that the proposed schemes are very effective (especially the one which employs Newton's method) in minimizing the EOG artifacts from contaminated EEG signals.

Performance Analysis of Reconstruction Techniques for Frequency-Domain Optical-Coherence Tomography

We address the issue of noise robustness of reconstruction techniques for frequency-domain optical-coherence tomography (FDOCT). We consider three reconstruction techniques: Fourier, iterative phase recovery, and cepstral techniques. We characterize the reconstructions in terms of their statistical bias and variance and obtain approximate analytical expressions under the assumption of small noise. We also perform Monte Carlo analyses and show that the experimental results are in agreement with the theoretical predictions. It turns out that the iterative and cepstral techniques yield reconstructions with a smaller bias than the Fourier method. The three techniques, however, have identical variance profiles, and their consistency increases linearly as a function of the signal-to-noise ratio.

Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

Search for a Light Higgs Boson in Central Exclusive Diffraction: Method and Detectors

By detecting leading protons produced in the Central Exclusive Diffractive process, p+p → p+X+p, one can measure the missing mass, and scan for possible new particle states such as the Higgs boson. This process augments - in a model independent way - the standard methods for new particle searches at the Large Hadron Collider (LHC) and will allow detailed analyses of the produced central system, such as the spin-parity properties of the Higgs boson. The exclusive central diffractive process makes possible precision studies of gluons at the LHC and complements the physics scenarios foreseen at the next e+e− linear collider. This thesis first presents the conclusions of the first systematic analysis of the expected precision measurement of the leading proton momentum and the accuracy of the reconstructed missing mass. In this initial analysis, the scattered protons are tracked along the LHC beam line and the uncertainties expected in beam transport and detection of the scattered leading protons are accounted for. The main focus of the thesis is in developing the necessary radiation hard precision detector technology for coping with the extremely demanding experimental environment of the LHC. This will be achieved by using a 3D silicon detector design, which in addition to the radiation hardness of up to 5×10^15 neutrons/cm2, offers properties such as a high signal-to- noise ratio, fast signal response to radiation and sensitivity close to the very edge of the detector. This work reports on the development of a novel semi-3D detector design that simplifies the 3D fabrication process, but conserves the necessary properties of the 3D detector design required in the LHC and in other imaging applications.

Scattering and Refraction as Contrast Mechanisms in X-Ray Imaging

Differentiation of various types of soft tissues is of high importance in medical imaging, because changes in soft tissue structure are often associated with pathologies, such as cancer. However, the densities of different soft tissues may be very similar, making it difficult to distinguish them in absorption images. This is especially true when the consideration of patient dose limits the available signal-to-noise ratio. Refraction is more sensitive than absorption to changes in the density, and small angle x-ray scattering on the other hand contains information about the macromolecular structure of the tissues. Both of these can be used as potential sources of contrast when soft tissues are imaged, but little is known about the visibility of the signals in realistic imaging situations. In this work the visibility of small-angle scattering and refraction in the context of medical imaging has been studied using computational methods. The work focuses on the study of analyzer based imaging, where the information about the sample is recorded in the rocking curve of the analyzer crystal. Computational phantoms based on simple geometrical shapes with differing material properties are used. The objects have realistic dimensions and attenuation properties that could be encountered in real imaging situations. The scattering properties mimic various features of measured small-angle scattering curves. Ray-tracing methods are used to calculate the refraction and attenuation of the beam, and a scattering halo is accumulated, including the effect of multiple scattering. The changes in the shape of the rocking curve are analyzed with different methods, including diffraction enhanced imaging (DEI), extended DEI (E-DEI) and multiple image radiography (MIR). A wide angle DEI, called W-DEI, is introduced and its performance is compared with that of the established methods. The results indicate that the differences in scattered intensities from healthy and malignant breast tissues are distinguishable to some extent with reasonable dose. Especially the fraction of total scattering has large enough differences that it can serve as a useful source of contrast. The peaks related to the macromolecular structure come to angles that are rather large, and have intensities that are only a small fraction of the total scattered intensity. It is found that such peaks seem to have only limited usefulness in medical imaging. It is also found that W-DEI performs rather well when most of the intensity remains in the direct beam, indicating that dark field imaging methods may produce the best results when scattering is weak. Altogether, it is found that the analysis of scattered intensity is a viable option even in medical imaging where the patient dose is the limiting factor.

Performance of Quantized Equal Gain Transmission With Noisy Feedback Channels

In this paper, new results and insights are derived for the performance of multiple-input, single-output systems with beamforming at the transmitter, when the channel state information is quantized and sent to the transmitter over a noisy feedback channel. It is assumed that there exists a per-antenna power constraint at the transmitter, hence, the equal gain transmission (EGT) beamforming vector is quantized and sent from the receiver to the transmitter. The loss in received signal-to-noise ratio (SNR) relative to perfect beamforming is analytically characterized, and it is shown that at high rates, the overall distortion can be expressed as the sum of the quantization-induced distortion and the channel error-induced distortion, and that the asymptotic performance depends on the error-rate behavior of the noisy feedback channel as the number of codepoints gets large. The optimum density of codepoints (also known as the point density) that minimizes the overall distortion subject to a boundedness constraint is shown to be the same as the point density for a noiseless feedback channel, i.e., the uniform density. The binary symmetric channel with random index assignment is a special case of the analysis, and it is shown that as the number of quantized bits gets large the distortion approaches the same as that obtained with random beamforming. The accuracy of the theoretical expressions obtained are verified through Monte Carlo simulations.

A unified construction of space-time codes with optimal rate-diversity tradeoff

The problem of constructing space-time (ST) block codes over a fixed, desired signal constellation is considered. In this situation, there is a tradeoff between the transmission rate as measured in constellation symbols per channel use and the transmit diversity gain achieved by the code. The transmit diversity is a measure of the rate of polynomial decay of pairwise error probability of the code with increase in the signal-to-noise ratio (SNR). In the setting of a quasi-static channel model, let n(t) denote the number of transmit antennas and T the block interval. For any n(t) <= T, a unified construction of (n(t) x T) ST codes is provided here, for a class of signal constellations that includes the familiar pulse-amplitude (PAM), quadrature-amplitude (QAM), and 2(K)-ary phase-shift-keying (PSK) modulations as special cases. The construction is optimal as measured by the rate-diversity tradeoff and can achieve any given integer point on the rate-diversity tradeoff curve. An estimate of the coding gain realized is given. Other results presented here include i) an extension of the optimal unified construction to the multiple fading block case, ii) a version of the optimal unified construction in which the underlying binary block codes are replaced by trellis codes, iii) the providing of a linear dispersion form for the underlying binary block codes, iv) a Gray-mapped version of the unified construction, and v) a generalization of construction of the S-ary case corresponding to constellations of size S-K. Items ii) and iii) are aimed at simplifying the decoding of this class of ST codes.

Online client-AP association in WLANs

In many IEEE 802.11 WLAN deployments, wireless clients have a choice of access points (AP) to connect to. In current systems, clients associate with the access point with the strongest signal to noise ratio. However, such an association mechanism can lead to unequal load sharing, resulting in diminished system performance. In this paper, we first provide a numerical approach based on stochastic dynamic programming to find the optimal client-AP association algorithm for a small topology consisting of two access points. Using the value iteration algorithm, we determine the optimal association rule for the two-AP topology. Next, utilizing the insights obtained from the optimal association ride for the two-AP case, we propose a near-optimal heuristic that we call RAT. We test the efficacy of RAT by considering more realistic arrival patterns and a larger topology. Our results show that RAT performs very well in these scenarios as well. Moreover, RAT lends itself to a fairly simple implementation.

Modified linear prediction method for directions of arrival estimation of narrow-band plane waves

A modified linear prediction (MLP) method is proposed in which the reference sensor is optimally located on the extended line of the array. The criterion of optimality is the minimization of the prediction error power, where the prediction error is defined as the difference between the reference sensor and the weighted array outputs. It is shown that the L2-norm of the least-squares array weights attains a minimum value for the optimum spacing of the reference sensor, subject to some soft constraint on signal-to-noise ratio (SNR). How this minimum norm property can be used for finding the optimum spacing of the reference sensor is described. The performance of the MLP method is studied and compared with that of the linear prediction (LP) method using resolution, detection bias, and variance as the performance measures. The study reveals that the MLP method performs much better than the LP technique.

Optical Tweezers for Single Molecule Biology

Molecular machinery on the micro-scale, believed to be the fundamental building blocks of life, involve forces of 1-100 pN and movements of nanometers to micrometers. Micromechanical single-molecule experiments seek to understand the physics of nucleic acids, molecular motors, and other biological systems through direct measurement of forces and displacements. Optical tweezers are a popular choice among several complementary techniques for sensitive force-spectroscopy in the field of single molecule biology. The main objective of this thesis was to design and construct an optical tweezers instrument capable of investigating the physics of molecular motors and mechanisms of protein/nucleic-acid interactions on the single-molecule level. A double-trap optical tweezers instrument incorporating acousto-optic trap-steering, two independent detection channels, and a real-time digital controller was built. A numerical simulation and a theoretical study was performed to assess the signal-to-noise ratio in a constant-force molecular motor stepping experiment. Real-time feedback control of optical tweezers was explored in three studies. Position-clamping was implemented and compared to theoretical models using both proportional and predictive control. A force-clamp was implemented and tested with a DNA-tether in presence of the enzyme lambda exonuclease. The results of the study indicate that the presented models describing signal-to-noise ratio in constant-force experiments and feedback control experiments in optical tweezers agree well with experimental data. The effective trap stiffness can be increased by an order of magnitude using the presented position-clamping method. The force-clamp can be used for constant-force experiments, and the results from a proof-of-principle experiment, in which the enzyme lambda exonuclease converts double-stranded DNA to single-stranded DNA, agree with previous research. The main objective of the thesis was thus achieved. The developed instrument and presented results on feedback control serve as a stepping stone for future contributions to the growing field of single molecule biology.

Voluntary Energy Harvesting Relays and Selection in Cooperative Wireless Networks

The use of energy harvesting (EH) nodes as cooperative relays is a promising and emerging solution in wireless systems such as wireless sensor networks. It harnesses the spatial diversity of a multi-relay network and addresses the vexing problem of a relay's batteries getting drained in forwarding information to the destination. We consider a cooperative system in which EH nodes volunteer to serve as amplify-and-forward relays whenever they have sufficient energy for transmission. For a general class of stationary and ergodic EH processes, we introduce the notion of energy constrained and energy unconstrained relays and analytically characterize the symbol error rate of the system. Further insight is gained by an asymptotic analysis that considers the cases where the signal-to-noise-ratio or the number of relays is large. Our analysis quantifies how the energy usage at an EH relay and, consequently, its availability for relaying, depends not only on the relay's energy harvesting process, but also on its transmit power setting and the other relays in the system. The optimal static transmit power setting at the EH relays is also determined. Altogether, our results demonstrate how a system that uses EH relays differs in significant ways from one that uses conventional cooperative relays.

Focal plane analysis of the Knox-Thompson algorithm in speckle interferometry

For the specific case of binary stars, this paper presents signal-to-noise ratio (SNR) calculations for the detection of the parity (the side of the brighter component) of the binary using the double correlation method. This double correlation method is a focal plane version of the well-known Knox-Thompson method used in speckle interferometry. It is shown that SNR for parity detection using double correlation depends linearly on binary separation. This new result was entirely missed by previous analytical calculations dealing with a point source. It is concluded that, for magnitudes relevant to the present day speckle interferometry and for binary separations close to the diffraction limit, speckle masking has better SNR for parity detection.