Projection Filter Research Articles

Multi-objective optimal design of microchannel cooling heat sink using topology optimization method

This article presents a density-based topology optimization (TO) method for a coupled thermal-fluid problem, in which the Navier-Stokes and heat transport equations are coupled. The two-dimensional microchannel heat sink model with fixed solid heat generation plates based on TO method is developed. These devices, such as air-cooled heat sinks, have recently attracted considerable attention in engineering applications of thermal cooling devices. The high-performance and functional diversification cooling devices are obtained by the proposed optimization method in this research. An optimal design problem is formulated as a multi-objective optimization problem, which includes heat resistance, energy dissipation and pressure drop. In the numerical implementation, Helmholtz-type Partial Differential Equation (PDE) based filter and smoothed Heaviside projection filter are utilized to produce discrete solutions, thus solving ill-posedness. Furthermore, TO result of channel layout obtained for a microchannel heat sink design is presented as an example to illustrate the validity of design methodology. Finally, several numerical examples are provided to study the effects of the weighting coefficient changes on the optimal results.

Cognitive Imagery Classification of EEG Signals using CSP-based Feature Selection Method

This paper presents a novel approach of spectral feature selection using spatial filters for the classification of four cognitive imagery tasks. The input dataset consists of electroencephalogram (EEG) signals acquired through a commercial wireless headset. The spectral features included mel frequency (MF) components extracted from the low frequency bands of EEG signal. A spatial projection filter was used for the selection of the most relevant features before classification. The popular method of multiclass common spatial pattern (CSP) and regularized CSP (RCSP) are investigated for a subject dependent (intra) and subject independent (inter) generation of spatial projection filter, respectively. Based upon this, present study used two different algorithmic approaches namely MF-CSP and MF-RCSP. The developed algorithm successfully classified four imagery actions with the reported prediction accuracy of 46.23% and 64.01% and standard deviation of 11.60% and 8.67% for MF-CSP and MF-RCSP, respectively.

Heaviside-Based Morphological Filters for Topology Optimization

To ensure manufacturability and mesh independence in density-based topology optimization schemes, it is imperative to use restriction methods. This paper proposes a family of Heaviside-based morphological filters based on the morphology-based restriction schemes, namely open, close, open-close and close-open filters. In the proposed morphological filters, Heaviside projection filter plays the role of dilation filter and modified Heaviside projection filter acts as the erosion filter. They work as principle operators and then applied sequentially to form the close, open, close-open, and open-close filters. The proposed morphological filters are tested by the compliance minimization problem. Test results show that the proposed four filters are volume preserving, and the characteristics of each filter are discussed.

Calculation and Analysis of the Pulse Response of Spatially Non-Invariant Projection Systems

Characteristics of spatially non-invariant telecentric projection systems, which are widely used in practice, are considered within the framework of wave optics. In the class of the Fresnel functions, the pulse response of the system is precisely calculated for various values of the projection objective and filter apertures. It is found that the response consists of two components, which determine the invariant and non-invariant properties of the system, respectively. Based on the approximation of the Fresnel function by elementary functions proposed previously by the author, an analytical expression for the pulse response is derived for the first time, and the response behavior is studied for various relationships of the objective and filter apertures. The correctness of choosing the parameters of the known quasi-invariant optical systems is analyzed. Recommendations on choosing the filter aperture are given to improve their spatially invariant characteristics. In contrast to available optical and geometrical methods, the proposed approach allows one to obtain reliable information about the character of wave field transformations in the considered systems.

An exponential quantum projection filter for open quantum systems

An approximate exponential quantum projection filtering scheme is developed for a class of open quantum systems described by Hudson–Parthasarathy quantum stochastic differential equations, aiming to reduce the computational burden associated with online calculation of the quantum filter. By using a differential geometric approach, the quantum trajectory is constrained in a finite-dimensional differentiable manifold consisting of an unnormalized exponential family of quantum density operators, and an exponential quantum projection filter is then formulated as a number of stochastic differential equations satisfied by the finite-dimensional coordinate system of this manifold. A convenient design of the differentiable manifold is also presented through reduction of the local approximation errors, which yields a simplification of the quantum projection filter equations. It is shown that the computational cost can be significantly reduced by using the quantum projection filter instead of the quantum filter. It is also shown that when the quantum projection filtering approach is applied to a class of open quantum systems that asymptotically converge to a pure state, the input-to-state stability of the corresponding exponential quantum projection filter can be established. Simulation results from an atomic ensemble system example are provided to illustrate the performance of the projection filtering scheme. It is expected that the proposed approach can be used in developing more efficient quantum control methods.

An inter user interference cancellation scheme for two users in full-duplex MIMO system

The inter-user interference is a critical performance degradation factor in a full-duplex multi-user system. However, the conventional pre-processing filters, such as null space projection filter and regularized channel inversion filter, are unsuitable for user pre-processing filter when each user has the same number of transmit and receive antennas. Thus, we propose an inter-user-interference cancellation scheme applicable to the users with the same number of transmit and receive antennas. By summing the received signals for two symbol periods, the proposed scheme can cancel inter-user interference and obtain a twofold diversity order. The simulation results show that the proposed scheme obtains higher spectral efficiency than the half-duplex system.

Improving random forests by neighborhood projection for effective text classification

In this article, we propose a lazy version of the traditional random forest (RF) classifier (called LazyNN_RF), specially designed for highly dimensional noisy classification tasks. The LazyNN_RF “localized” training projection is composed by examples that better resemble the examples to be classified, obtained through nearest neighborhood training set projection. Such projection filters out irrelevant data, ultimately avoiding some of the drawbacks of traditional random forests, such as overfitting due to very complex trees, especially in high dimensional noisy datasets. In sum, our main contributions are: (i) the proposal and implementation of a novel lazy learner based on the random forest classifier and nearest neighborhood projection of the training set that excels in automatic text classification tasks, as well as (ii) a throughout and detailed experimental analysis that sheds light on the behavior, effectiveness and feasibility of our solution. By means of an extensive experimental evaluation, performed considering two text classification domains and a large set of baseline algorithms, we show that our approach is highly effective and feasible, being a strong candidate for consideration for solving automatic text classification tasks when compared to state-of-the-art classifiers.

Nonlinear Acoustic Echo Cancellation Based on Multichannel Adaptive Filters: A Novel Approach

This paper presented a new class of non-linear adaptive filters, whose structure is based on Hammerstein model. Such filters designed from the functional link adaptive filter (FLAF) model, described by a non-linear input expansion which develops the illustration of the input signal through a projection in a higher dimensional space and a subsequent adaptive filtering. In order to give toughness against different degrees of non-linearity, a collaborative FLAF is proposed based on the adaptive combination of filters. Such architecture provided the best performance regardless of the nonlinearity degree in the echo path. Particularly this architecture can accomplish the linear and non-linear filters. Such as Normalized least mean square algorithm using FDAF, Affine projection and Lattice filters are used. When comparing their Echo return loss enhancement performance, Affine projection algorithm gives 20 dB more than others in this work.

Transmitter/receiver polarisation optimisation based on oblique projection filtering for mainlobe interference suppression in polarimetric multiple‐input–multiple‐output radar

Controlling the polarisation states of the transmitter and the receiver enables improving the performance of radar systems, especially for mainlobe interference suppression applications. In this study, the authors consider the design of optimal polarisations at both of the radar transmitter and receiver for mainlobe interference suppression. They propose the polarimetric multiple-input-multiple-output (MIMO) radar which combines the advantages of MIMO systems with the advantages offered by optimally choosing the transmitter polarisation or the receiver polarisation to achieve a better anti-jamming performance. The polarisation diversity is employed in the transmit array and the receive array. The interferences can be suppressed by the oblique projection filter. Based on the output signal-to-interference-plus-noise ratio analysis, the optimal transmitter polarisation and the receiver polarisation can be obtained. Simulation results demonstrate that interference can be effectively suppressed with the radar configuration, and better interference suppression performance can be achieved with the optimal transmitter polarisation and receiver polarisation.

Topology optimization of three-phase interpolation models in Darcy-stokes flow

This paper extends the topology optimization (TO) methods of fluid flows to design the three-phase (i.e. solid, fluid and porous materials) interpolation scheme. In addition to numerous studies about the optimized layout of regions governed by Darcy-Stokes equations, this paper aims to minimize the pressure attenuation in multiple phase interpolation models. The optimized distribution is obtained by considering both the fluid permeability through the porous media and impenetrable inner walls (solid phase) and neglecting buoyancy and other external body forces. Each material phase is assigned with two design variables that are projected into the element space via the regularized interpolation functions. The solid isotropic material with penalization (SIMP) interpolation functions, which is initially developed for minimizing compliance of multiple structural materials, is applied to TO processes of Darcy–Stokes flow. The fields are divided into the design and non-design domains, and TO layouts are assembled to satisfy the given performance functions. The smoothed Heaviside projection filter and Helmholtz-type Partial Differential Equation (PDE) based filter are utilized to produce discrete solutions in the continuum TO processes. Numerical studies are carried out to verify the proposed interpolation scheme.

Projection smoothing for continuous and continuous-discrete stochastic dynamic systems

This study investigates the states of continuous and continuous-discrete time nonlinear stochastic dynamic systems conditioned on noisy measurements. We adopt a differential geometric approach to construct finite-dimensional algorithms for solving the filtering and smoothing problems associated with such systems. In particular, we use a projection method based on the Hellinger distance and the related Fisher metric to derive a novel backward equation that is satisfied by the approximate probability density associated with the smoothing problem. Finally, by combining our approach with a previously developed projection filter, we formulate a finite-dimensional approximation of the forward (filtering) and backward (smoothing) algorithms on the basis of the above-mentioned projection method.

Multiresolution topology optimization using isogeometric analysis

SummaryThe paper introduces a novel multiresolution scheme to topology optimization in the framework of the isogeometric analysis. A new variable parameter space is added to implement multiresolution topology optimization based on the Solid Isotropic Material with Penalization approach. Design density variables defined in the variable space are used to approximate the element analysis density by the bivariate B‐spline basis functions, which are easily obtained using k‐refinement strategy in the isogeometric analysis. While the nonuniform rational B‐spline basis functions are used to exactly describe geometric domains and approximate unknown solutions in finite element analysis. By applying a refined sensitivity filter, optimized designs include highly discrete solutions in terms of solid and void materials without using any black and white projection filters. The Method of Moving Asymptotes is used to solve the optimization problem. Various benchmark test problems including plane stress, compliant mechanism inverter, and 2‐dimensional heat conduction are examined to demonstrate the effectiveness and robustness of the present method.

Reduced‐dimension DOD and DOA estimation through projection filtering in bistatic MIMO radar with jammer discrimination

This study presents a novel computationally efficient method for estimating the direction of departure (DOD) and direction of arrival (DOA) of targets and discriminates the DOA of jammer signals for a bistatic multiple-input, multiple-output (MIMO) radar system. Using properly designed projection filters, the proposed method replaces expensive exhaustive two-dimensional angle search with several one-dimensional angle search algorithms. The proposed method estimates DOD–DOA pairs of targets and discriminates jamming signals successfully regardless of the jamming signal strength. The performance of the proposed method is confirmed by simulation results.

Multi‐domain collaborative filter for interference suppressing

Filters with antenna arrays are widely used for interference suppression in the temporal domain, frequency domain, space domain and so on. Meanwhile, the interference mitigation performance of a single-domain-based filter depends on a noticeable difference between the target signal and interference in the corresponding domain. However, the interference cannot be efficiently suppressed by a single-domain-based filter when the difference in this individual domain is small. To solve this problem, a multi-domain collaborative oblique projection filter is proposed in this study. First, multi-domain spaces are theoretically derived to distinguish the target signal and the interference, and then a multi-domain oblique projection operator is provided to recover the original target and suppress the interference. Depending on the multi-domain spaces, the filter has excellent performance when the difference is insignificant in each individual domain, whereas the performances of the single-domain-based filter and cascade filter degrade significantly. Finally, a space–polarisation–frequency domain collaborative filter based on oblique projection is given as an illustration. Performance analysis and simulation results are provided to illustrate the superiority of the proposed filter for interference mitigation.

Hybrid Approach to Single-Channel Speech Separation Based on Coherent–Incoherent Modulation Filtering

Single-channel speech separation is a challenging problem that has been of particular interest in recent years. Here the goal is to separate the target speech signal from the interference signals, with high accuracy. We propose a new hybrid single-channel speech separation system that applies adaptive coherent modulation filtering for low-frequency subbands and iterative incoherent speech separation technique for high-frequency subbands. In the adaptive coherent modulation filtering, an affine projection filter is applied to subband envelope in order to eliminate the interference signal. The subband envelope is determined via demodulation of the subband signal using a coherently detected subband carrier based on the time-dependent spectral center-of-gravity demodulation. The adaptive affine projection filter uses the separated target signal obtained from the iterative incoherent speech separation system as a reference signal. This system first obtains a rough estimate of target fundamental frequency range and then uses this estimate to segregate target speech. It then improves both fundamental frequency range estimation and voiced speech separation iteratively. Perceptual evaluation of speech quality, as one of the evaluation indices investigated in this paper, indicates that the proposed system extracts the majority of target speech segments with minimal interference and outperforms previous systems in voiced speech separation.

Compound identification using random projection for gas chromatography–mass spectrometry data

In general, compound identification through library searching is performed on original mass spectral space by using some developed similarity measure. More powerful similarity measure need more computational time. In order to reduce computational time, the original mass spectral space was transformed into binary space by random projection. The hamming distance between query and reference the vector of binary space are calculated. In this study, Mass Spectral Library 2005 (NIST05) main library containing 163,195 mass spectra is used as reference database. The replicate library containing 23,290 mass spectra is used as query data. The proposed method was used to compare with existing five similarity measures. Among two proposed performance criteria, composite semi-partial similarity measure achieve the best identification accuracy, then follow the random projection. When the binary number of random projection set as 2176 bits, the identification accuracy of rank 1 reach to 83.1%. If only considering computational time, random projection is the most rapid approach among five algorithms. Therefore, random projection can be also used as a filter to create searching sub-library for other complicated similarity measures. A series experiments are conducted by using random projection filter, the experimental results show the computational time of other similarity measure is reduced and the identification performance is not sacrificed.

Real-Time Reconstruction of Multimode Tip Motion of Microcantilevers in Dynamic Atomic Force Microscopy

A modal projection filtering method is proposed for the dynamic atomic force microscopy (AFM) to accurately reconstruct the multimode tip motion of the AFM microcantilever from the single measurement signal of the optical lever method in real time. The optical lever method is inherently a slope detection method, wherein each individual dynamic mode pertinent to the slope detection principle of the measurement system has its own distinct measurement sensitivity because of the unique dynamic mode shape per a mode. The proposed modal projection filtering method uses the experimentally identified multimode dynamic model of the AFM microcantilever along with the calibrated measurement sensitivities of individual dynamic modes to design the modal projection filters to extract the responses of individual dynamic modes from the single measurement signal. The tip motion of the AFM microcantilever is then accurately reconstructed by using a linear superposition of the extracted responses of multiple dynamic modes. The designed modal projection filters were implemented in a field programmable gate array for real-time computation with an update rate of 1 MHz. Computer simulations and experimental investigations were performed to validate the principle of and to demonstrate the performance of the proposed method.

Trilinear decomposition‐based spatial‐polarisational filter method for deception jamming suppression of radar

This study focuses on the problem of deception jamming suppression for a radar system and an effective spatial-polarisational filter strategy is outlined based on the spatial and polarisational parameter joint estimates. It can make the false target filtered effectively and the desired target remained with an improved signal-to-jammer-noise ratio. In this scheme, the trilinear decomposition model is first employed to obtain paired 2D direction of arrive and polarisation parameter joint estimates of the target and jammer. Then a spatial-polarisational oblique projection filter operator based on the joint estimates is constructed and utilised to project the received mixed return of radar onto to the target echo sublinear space so as to suppress the jamming. Meanwhile, the complexity of the above jamming suppression algorithm is presented and the working flow of a radar system equipped with a polarisation sensitive array for countering the deception jammer is also presented. Simulation results demonstrate the performance of the proposed scheme.

Range-Based Underwater Vehicle Localization in the Presence of Unknown Ocean Currents: Theory and Experiments

This paper addresses the problem of range-based autonomous underwater vehicle (AUV) localization in the presence of unknown ocean currents. In the setup adopted, the AUV is equipped with an attitude and heading reference system, a depth sensor, and an acoustic device that provides measurements of its distance to a set of stationary beacons. We consider the situation where the number of active beacons is not known in advance and may vary with time. The objective is to simultaneously localize the AUV and beacons, that is, to find their positions underwater. We start by deriving conditions under which it is possible to reconstruct the initial condition of the system under study. We consider the design model where the states evolve continuously with time, but the range measurements are only available at discrete instants of time, possibly in a nonuniform manner. For trimming maneuvers that correspond to AUV trajectories with constant linear and angular velocities expressed in the body frame, we show that if either the position of one of the beacons or the initial position of the AUV is known, then even without depth information the system is weakly observable (i.e., the set of states that are indistinguishable from a given initial configuration contains only a set of finite isolated points). If depth measurements are also available, then the system is observable even in the presence of unknown constant ocean currents. Equipped with these results, we then propose a novel observer for simultaneous AUV and beacon localization. The mathematical setup exploited borrows from minimum-energy estimation theory applied to continuous-time processes with discrete measurements, projection filters, and multiple-model estimation techniques. Convergence analysis of the resulting observer system yields conditions under which the estimation errors converge to a small neighborhood of the origin (whose size depends on the magnitude of the process and measurement noise). The results of field experiments with a robotic marine vehicle show the efficacy of the simultaneous AUV/multiple beacon localization system proposed.

Nonlinear projection filter for target tracking using range sensor & optical tracker

Target tracking filters have a variety of applications in various areas. Typically, a radar provides the range measurement and an optical sensor measures the orientation of a target. The measurements provided by the sensors have very strong nonlinearities with the states of the target given in the Cartesian coordinates while its dynamics is linear parameter time-varying. The time-varying component exists because of the unknown acceleration input in the target. Nonlinear projection filter provides a solution to the nonlinear estimation problem by approximating the solution as a linear combination of orthogonal basis functions. The analytic expression for propagating the joint probability density function is derived for the target tacking problem and this reduces large amount of computation times, where the filter equations are normally obtained numerically. The effectiveness of the filter is demonstrated by a numerical simulation.