Programmable hardware implementation for the median-rational hybrid filters

A new class of nonlinear filters, the so-called class of Multi-Directional Infinite Impulse Response Median Hybrid Filters (MIMH), is presented and analyzed. The input signal is processed twice using a Linear Shift-Invariant (LSI) Infinite Impulse Response (IIR) filtering module: once with normal causality and a second time with inverted causality. The final output of the MIMH filter is the median of the two directional outputs and the original input signal. Thus, the MIMH filter is a concatenation of linear filtering (a LSI IIR filtering module) and nonlinear filtering (a median filtering module). Because of this unique scheme, the MIMH filter possesses many desirable properties (including impulse removal, step preservation, and noise suppression). >

A Linear Method for the Design of Optimal Nonlinear Filters for Non-Gaussian Processes

In this letter, a new class of nonlinear filters called vector median-rational hybrid filters (VMRHFs) for multispectral image processing is introduced and applied to the color image filtering problem. These filters are based on rational functions (RFs) offering a number of advantages. First, a rational function is a universal approximator and a good extrapolator. Second, it can be trained by a linear adaptive algorithm. Third, it produces the best approximation (w.r.t. a given cost function) for some specific functions. The output is the result of a vector rational operation over the output of three subfilters, such as two vector median (VM) subfilters and one center weighted vector median filter (CWVMF). These filters exhibit desirable properties, such as edge and details preservation and accurate chromaticity estimation.

A new class of nonlinear filters called FIR-weighted myriad hybrid (FIR-WMyH) filters was introduced. These filters have a combination structure of linear FIR filters and weighted myriad filter, and can efficiently utilize the special strongpoint of two filters. Through the backpropagation algorithm used in the neural networks, we derive a stochastic gradient-based adaptive algorithm for determining optimal FIR-WMyH filters under the mean square error (MSE) criterion. In two impulsive noise models, the robust performance of this adaptive algorithm is demonstrated through the computer simulation results. © 2006 IEEE.

Through the combination of linear finite impulse response (FIR) filters and weighted order statistic (WOS) filters, the authors introduce a new class of nonlinear filters called FIR-WOS hybrid (FWH) filters. This class of filters, including FIR filters, WOS filters, and various kinds of FIR median hybrid (FMH) filters, consists of a few linear FIR subfilters and a WOS filter operated over the outputs of the subfilters. Motivated by the backpropagation algorithm used in neural networks, an adaptive algorithm is derived in the binary domain for determining optimal FWH filters under the mean absolute error criterion. Simulation results in image processing demonstrate that adaptive FWH filters perform as well as linear filters in Gaussian noise and better than adaptive WOS filters in impulsive noise. >

Impulse noise (IN) affects the digital image, during transmission, digital storage, and image acquisition. IN removal from an image is necessary as it retains the quality of the image. This work concentrates on the IN. A neuro‐fuzzy (NF) system based on a fuzzy technique which is trained by a learning algorithm derived from neural network theory was implemented for the removal of noise. A NF network for noise filtering in grayscale images that combines two NF filters with a postprocessor to produce the output was presented. However, Sugeno‐type is not intuitive technique and it also less accurate. To overcome these problems, a hybrid NF filter with optimized intelligent water drop (IWD) technique is introduced, where hybridized Sugeno–Mamdani‐based fuzzy interference system is implemented in both the NF filters to obtain more efficient noise removal system. To improve the accuracy of the assignment of membership values to each input pixels, the optimized IWD technique is utilized, as the choice of membership function decides the efficiency of the noise removal in the images. Here, Fuzzy rules have been used to obtain the filtered output. The Hybrid method maintains the accuracy of the Sugeno model and also the interpretable capability of the Mamdani model. This method is robust against the IN and it is flexible, efficient, and accurate than existing filtering method in both noise attenuation and detail preservation and it has a great scope for better real‐time applications.

The noise attenuation properties of an acoustic liner consisting of Helmholtz resonators with extended necks (HRENs) are investigated. An optimal liner constructed by 16 inhomogeneous HRENs is designed to be effective in sound absorption in a prescribed frequency range from 700 to 1000 Hz. Its quasi-perfect absorption capability (average absorption coefficient above 0.9) is validated by measurements and simulations. The resonance frequencies of the individual resonators in the designed liner are just located within the effective absorption bandwidth, indicating the overlapping phenomenon of absorption peaks. In addition, the liner maintains a thin thickness, about 1/25th with respect to the longest operating wavelengths. To assess the acoustic performance of the designed liner in the presence of mean flow, experimental investigations are performed in a flow tube. Results show a near flat transmission loss is attained in the target frequency range by the designed liner. Additionally, the impedance of the uniform HREN-based liner is extracted at flow condition. In all, the inhomogeneous HREN-based liner is featured by the thin thickness and the excellent wide-band noise attenuation property. These features make the designed liner an promising solution for noise attenuation in both static and flow conditions.

The practical issues in the design and implementation of the optimal binary filters limit the observation windows down to a size that is usually much smaller than the characteristic features found in document images. To overcome this drawback, a new composite binary filtering method is developed. A preprocessing stage based on linearly separable Boolean functions is used to gather information from a very large window. The pre-filtering results together with the pixel values from a smaller window are then faded into an optimal estimator. The proposed filter structure can be viewed either as a two stage binary filter with linearly separable preprocessing or as a locally adaptive binary filter where the local adaptation is based on the characteristic features extracted from a large window. Both software and hardware implementations of the filter exhibit reasonable complexity even for large windows. Some properties of the filter and a closed form expression of the mean-absolute-error are derived. It is shown that, because there are no restrictions in the second stage, the whole composite structure can be optimally designed. The paper develops a practical design procedure that uses an efficient gradient method. Computer simulations are used to test the proposed filter against the optimal binary filter.

Fault seismic attribute volumes (such as volumetric coherence and curvature) represent an efficient and objective way to visualize and identify faults in seismic cubes. Fault geometric attributes such as length, height, and fault segmentation can be extracted from such fault seismic attribute volumes. We evaluate the strengths and pitfalls of using coherence volumes for characterization of fault geometry. The results are obtained using a database from the Barents Sea, which contains 35 3D seismic cubes, together with conceptual synthetic seismic models. A high signal-to-noise ratio is a requirement for the extraction of accurate fault geometric data. Noise attenuation methods improve fault visualization, but our results indicate that the effect of noise attenuation on the extracted fault geometric attributes is only clear in areas of low signal-to-noise ratios. The choice of coherence algorithm is important when extracting fault length data. Semblance-based coherence performs better than gradient structure tensor-based coherence in low-displacement areas near the fault tips, and it produces more accurate fault length data. Faults can appear segmented in coherence volumes if relatively similar reflectors are juxtaposed across a fault. In such areas, it is important that the interpreter does not overlook the fault. The size of the analysis window used in coherence calculations controls the resolution and continuity of the imaged faults. Our results support an optimal temporal window size of one to two times the dominant period of the seismic data (typically 7–17 samples in conventional 4 ms sampled 3D seismic data). Larger temporal window sizes can result in an overestimation of fault height, especially for small faults. A large spatial window can smear out segmentation along the fault and make the fault traces wider. Even though a large spatial window can have some positive effects, we recommend using a relatively small spatial window (five traces) when extracting subtle fault geometric attributes.

The ever increasing demand for large quantities of bio-engineered pharmaceuticals and the tendency for doses to become larger stimulate the development of more productive and reliable mammalian cell culture technologies. In this context, perfusion bioreactors appear an efficient means to achieve high volumetric productivity and high product concentration. Since large-scale implementation of perfusion is limited by the reliability and scale-up potential of the device used to achieve cell retention, the present work proposes to tackle the problem bottom-up from the fundamentals of physics in order to develop, characterize and model novel particle retention strategies able to overcome the limitations of state-of-the-art systems. The first part of the present thesis focuses on the identification of physical force fields chosen for their ability to drive particles or cells into highly localized regions of a suspension. The ability of ultrasonic, dielectrophoretic and magnetophoretic interactions to make cells levitate over a surface was identified as an innovative way of implementing a Boycott effect (similar to that occurring in inclined sedimentation channels) while maintaining the flow channel in a vertical position. Therefore, inclined settlers were chosen as a reference system and the Ponder-Nakamura-Kuroda theory describing their performance was extended to take into account ultrasonic, dielectrophoretic and magnetic effects. The second part of the work provides deep modeling insight into the mechanisms underlying mammalian cell retention in these new filter implementations. Potentials and limitations are discussed in details. In particular, coupling dielectrophoresis with the Boycott effect proved to be successful in separating polystyrene particles from their moderately electrically conductive suspending medium. However, in highly conductive media, this process was shown to be very sensitive to order-disruptive electrokinetic effects such as ac electroosmosis and electrothermal fluid flow. Heat dissipation is however not specific to dielectrophoresis. This phenomenon is also a known limitation of the ultrasonic or magnetophoretic implementations, in certain conditions. The last part focused its work on the development of magnetophoretically-enhanced sedimentation, which was proposed as a means to partly overcome the heat dissipation problem observed with dielectrophoresis in highly conductive culture media. For such a magnetic approach to work correctly with intrinsically nonmagnetic materials, a paramagnetic suspending medium has to be used. The current implementation proposes to prepare media with fair quantities of gadolinium(III) or dysprosium(III) salts dissolved in them. Using such a paramagnetic buffer, the feasibility of magnetically retaining polystyrene particles could be verified in a vertical separation channel, hence providing first demonstration of the principle. The use of paramagnetic substances in mammalian cell culture media is naturally a matter of concern. The present work addresses this question as well and highlights the feasibility of growing Chinese Hamster Ovary cells in Gd(III)- or Dy(III)-rich environments. In contrast, attempts to develop low electrically conductive culture media failed and replacement of the NaCl content by D-mannitol or glycerol demonstrated severe growth inhibition effects.

Presents a novel neural-network-based predictor for received power level prediction in direct sequence code division multiple access (DS/CDMA) systems. The predictor consists of an adaptive linear element (Adaline) followed by a multilayer perceptron (MLP). An important but difficult problem in designing such a cascade predictor is to determine the complexity of the networks. We solve this problem by using the predictive minimum description length (PMDL) principle to select the optimal numbers of input and hidden nodes. This approach results in a predictor with both good noise attenuation and excellent generalization capability. The optimized neural networks are used for predictive filtering of very noisy Rayleigh fading signals with 1.8 GHz carrier frequency. Our results show that the optimal neural predictor can provide smoothed in-phase and quadrature signals with signal-to-noise ratio (SNR) gains of about 12 and 7 dB at the urban mobile speeds of 5 and 50 km/h, respectively. The corresponding power signal SNR gains are about 11 and 5 dB. Therefore, the neural predictor is well suitable for power control applications where ldquodelaylessrdquo noise attenuation and efficient reduction of fast fading are required.

An adaptive steganographic method based on the measurement of just noticeable distortion profile

The problem of extracting the desired signal from the recording of an array of sensors corrupted by multiple coherent interference and random noise is considered. The desired signal and interferences are assumed to have different arbitrary waveforms, and no a priori knowledge of such waveforms is assumed. The relative delay times of the interferences with respect to the desired signal are assumed to be known or can be accurately estimated. A vector of array filters is derived for the multichannel offline processing of the array recording with the objective of extracting the desired signal. These array filters achieve an all-pass condition for the desired signal, a strong suppression of the coherent interferences, and some degree of attenuation of the random noise. The tradeoff between suppressing the coherent interferences and attenuating the random noise is examined. An implementation of these array filters using the QR decomposition technique for rank determination is outlined. The ringing effect-sometimes observed in the output-is carefully analyzed as it relates to the residual coherent interferences. Two illustrative examples confirming the theoretical findings are presented. The third example is a preliminary investigation of the sensitivity of the results to estimation errors in the parameters of the coherent interferences.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The narrow bandgap of a seismic metamaterial dramatically limits its application in attenuating seismic waves for securing buildings. This research proposes an improved cylinder-type seismic metamaterial by introducing plus-shaped to widen the bandgap. The propagation of seismic waves through a three-dimensional sample of seismic metamaterial is calculated to show its efficiency of the earthquake shielding using the finite-element method based on Floquet-Bloch theory. By comparison to the common seismic metamaterial consisting of simple cylinder structures, it is found that our metamaterial based on cylinder with plus-shaped structures can yield a three times relative bandgap width for seismic surface waves, which is more suitable for practical applications. Moreover, the bandgap depends on the constraint of geometric parameters and elastic parameters, and can be easily tuned to higher frequency for other phenomena such as vibration and noise attenuation by tailoring those parameters.

A system‐level noise mitigation technique is used to design low‐noise single‐ended switched‐capacitor filters which implement noise shaping. The performance is comparable to that of a fully differential structure, while the complexity, power dissipation and chip area are drastically reduced.