Linear Phase Model Research Articles

Refined Multifrequency Interferometric SAR Phase Unwrapping for Extremely Steep Terrain

Multifrequency (MF) interferometric synthetic aperture radar (InSAR) phase unwrapping (PU) technology is proposed for PU in steep terrains where the phase changes of adjacent pixels exceed the commonly required threshold of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> . Traditional MF PU methods will fail in the case of extremely steep terrain such as artificial buildings due to insufficient quality of phase noise suppression (PNS). In this article, we propose a refined MF-InSAR PU method that can be robustly applied for extremely steep terrain PU via two main contributions. First, an additional steep edge extraction step is introduced for geological local PU window generation to prevent inaccurate PNS across the extracted steep edges. Second, the traditional linear phase model is extended to a nonlinear one for more accurate MF local fringe frequency estimation in PNS. The computer simulations and the real dual-frequency airborne experiment validate the presented approach.

Estimation of Modulation Index for Partial Response CPM Signal

Continuous phase modulation (CPM) is a power and bandwidth efficient modulation scheme used in cellular, personal, and satellite communications among other applications. If the modulation index of the CPM waveform used by the transmitter is unavailable at the receiver, serious performance degradation may occur. This paper investigates the problem of modulation index estimation for partial response continuous phase modulation schemes. Specifically, we propose two novel estimators for the CPM signal observed in an additive white Gaussian noise channel. A non-data aided method of moments (MoM) estimator based upon the fourth-order cumulants and a data-aided best linear unbiased estimator (BLUE) based upon an approximate linear phase model of the received CPM signal have been proposed. Modified Cramer-Rao lower bound is derived for the partial response CPM schemes to assess the performance of the estimators. We also perform numerical simulations to compare the mean-squared error (MSE) performance of the proposed MoM and BLUE estimators with previously proposed estimators in the literature. It is shown that the MoM estimator exhibits good MSE performance at low signal-to-noise ratio (SNR) while the BLUE estimator performs very well at high SNRs. Moreover, the proposed estimators have lower complexity than existing methods and are based upon non-iterative algorithms.

Competition between recently potentiated synaptic inputs reveals a winner-take-all phase of synaptic tagging and capture.

Canonical models suggest that mechanisms of long-term memory consist of a synapse-specific, protein synthesis-independent induction phase (changes in synaptic weights/temporary tagging of such synapses) and, within adjacent dendritic compartments, a protein synthesis-dependent distribution phase that may accompany or immediately precede induction and whose protein products enable consolidation through synaptic capture. We now report that this distribution phase is competitive in a "winner-take-all" fashion when synapses potentiated at induction compete with each other for plasticity-related proteins. This finding highlights the importance of synaptic competition in creating stable long-lasting memory in neural networks without disruption.

Motion‐compensated real‐time MR thermometry augmented by tracking coils

To develop and evaluate a real-time proton resonant frequency (PRF) based MR thermometry method with a novel motion compensation technique, using linear phase model and active tracking coils. A 6F catheter with multiple tracking coils and radiofrequency (RF) ablation tip was built for ex vivo experiments using excised bovine liver on a 1.5 Tesla scanner. A real-time MR acquisition scheme with interleaved active catheter tracking and multislice imaging was implemented. To evaluate the proposed method, in-plane periodic linear motion and through-plane irregular motion were induced by the rocker capability of the scanner and hand, respectively. Real-time temperature maps of the tissue undergoing a 2-min RF ablation cycle were obtained and used to compare the performance of the proposed method with that of the multi-baseline method. The temporal window achieved per acquisition of one slice and catheter tracking is ∼380 ms. The standard deviations of tracking errors are less than 1 mm for both irregular and periodic motions in x-y plane. The measurements at the heated and unheated regions demonstrate that the proposed thermometry method perform equally well for both in-plane and through-plane motion while maintaining a similar accuracy (σ = 1.10 versus 1.04°C) compared with the conventional multi-baseline method. The new MR thermometry method using catheter-based tracking coils and linear phase model for motion compensation and phase correction is promising and may offer reliable MR thermometry for real-time MRI-guided thermal therapies.

Improvement of the SNR and resolution of susceptibility-weighted venography by model-based multi-echo denoising

The vein structures of the brain are important for understanding brain function and structure, especially when functional magnetic resonance imaging (fMRI) is utilized, as fMRI is based on changes in the blood-oxygen-level-dependent (BOLD) signal, which is directly related to veins. The aim of the present study was to develop an effective method to produce high signal-to-noise-ratio (SNR) and high-resolution multi-contrast susceptibility-weighted (SW) images of vein structures from 3T magnetic resonance (MR) scanners using multi-gradient-echo MR acquisition and a successive denoising process for both magnitude and phase data. Successive multi-echo MR images were acquired at multiple time points using a multigradient-recalled echo sequence at 3T, and noise in the magnitude and phase data was effectively suppressed using model-based denoising methods. A T(2)* relaxation model was used to denoise the magnitude data and a linear phase model was used to denoise the phase data. SW venography images were obtained from the denoised MR data and compared with conventional SW venography. To evaluate the performance of our denoising methods, we conducted numerical simulation studies and compared the mean-squared-error (MSE), SNR, and contrast-to-noise ratio (CNR) that we obtained using our procedure with those obtained using conventional denoising methods. In addition, images were inspected visually. Numerical simulations showed that our proposed model-based denoising methods were the most effective at suppressing noise. In vivo experiments also showed a substantial increase in the SNR of the phase mask obtained using the proposed denoising process (twice that of the conventional GRE-based phase mask). The T(2)* relaxation model method improved the SNR of the magnitude image (1.17-1.35 times that of the GRE-based magnitude image). Noise suppression of both magnitude and phase data using our proposed method resulted in an overall increase in the SNR and CNR in the final SW venography (1.1-1.5-fold and 1.96-fold higher SNR and CNR, respectively, than that of the GRE-based SW venography). We demonstrated that high SNR and high-resolution SW venograms can be obtained using multi-echo gradient-recalled acquisition and successive model-based denoising of both magnitude and phase data.

Modeling both the magnitude and phase of complex-valued fMRI data

In MRI and fMRI, images or voxel measurement are complex valued or bivariate at each time point. Recently, (Rowe, D.B., Logan, B.R., 2004. A complex way to compute fMRI activation. NeuroImage 23 (3), 1078–1092) introduced an fMRI magnitude activation model that utilized both the real and imaginary data in each voxel. This model, following traditional beliefs, specified that the phase time course were fixed unknown quantities which may be estimated voxel-by-voxel. Subsequently, (Rowe, D.B., Logan, B.R., 2005. Complex fMRI analysis with unrestricted phase is equivalent to a magnitude-only model. NeuroImage 24 (2), 603–606) generalized the model to have no restrictions on the phase time course. They showed that this unrestricted phase model was mathematically equivalent to the usual magnitude-only data model including regression coefficients and voxel activation statistic but philosophically different due to it derivation from complex data. Recent findings by (Hoogenrad, F.G., Reichenbach, J.R., Haacke, E.M., Lai, S., Kuppusamy, K., Sprenger, M., 1998. In vivo measurement of changes in venous blood-oxygenation with high resolution functional MRI at .95 Tesla by measuring changes in susceptibility and velocity. Magn. Reson. Med. 39 (1), 97–107) and (Menon, R.S., 2002. Postacquisition suppression of large-vessel BOLD signals in high-resolution fMRI. Magn. Reson. Med. 47 (1), 1–9) indicate that the voxel phase time course may exhibit task related changes. In this paper, a general complex fMRI activation model is introduced that describes both the magnitude and phase in complex data which can be used to specifically characterize task related change in both. Hypotheses regarding task related magnitude and/or phase changes are evaluated using derived activation statistics. It was found that the Rowe–Logan complex constant phase model strongly biases against voxels with task related phase changes and that the current very general complex linear phase model can be cast to address several different hypotheses sensitive to different magnitude/phase changes.

Scheidel and Crowell revisited: a descriptive study of group proposal sequencing

In a landmark study, Scheidel and Crowell (1964) found evidence of two previously undescribed group discussional phenomena, “reach-testing,” or short sequences in which group members make, discuss, and evaluate a single proposal before moving on to another, and “spiraling,” or re-appearances later in discussion of proposals that had received positive evaluations when first discussed. The goal of the study reported here is to evaluate the generality of spiraling in a set of 87 group discussions. The results showed large variability among groups. Many groups spiraled little or not at all. A few groups spiraled substantially more than Scheidel and Crowell's model would suggest. These findings suggest that, as with the linear phase model, what was once considered to occur in all group discussions is in fact only valid for some. In addition, group discussion patterns were not associated with critical group output variables, providing evidence that the content of discussion matters much more than the order in which this content appears in discussion.

Frequency-selective FIR predictors

A simple heuristic method for designing frequency-selective finite impulse response (FIR) filters with prediction properties is presented. Starting from passband and stopband specifications, a linear-phase model filter is converted into a minimum phase equivalent and the zero locations are manipulated in order to achieve negative group delay at the zero frequency. The method allows us to design FIR ramp predictors with nearly equiripple stopband characteristics.

Embedding prevention services within systems of care: Strengthening the nexus for children

System-of-care models that offer a continuum of integrated mental health services for children are being widely implemented in local communities. Preventive services, arising from the theoretically grounded prevention sciences, are an important but neglected component of this model. Studies of the use of mental health services by children are reviewed, and an integrative model is proposed to incorporate prevention services as a component of the child mental health service system. Construction of the prevention sciences has followed a linear phase model that has advantages and disadvantages for bridging prevention sciences and services research. As prevention science progresses into broader field tests of its effectiveness, studies of child services can be informative, especially in advancing the applicability and dissemination of research findings. Future directions are outlined to strengthen the nexus between services research and prevention science, and to construct a new genre of prevention services research.

Carrier Phase Recovery for Two Dimensional Digital Communications

A carrier recovery scheme used for synchronous serial two-dimensional data transmission system is investigated. A decision-directed observation vector, formulated at baseband, permits use of this technique to arbitrary two-dimensional modulation schemes. The imphasis here is on obtaining carrier tracking loops based on the decision-directed observations, which would perform well even when the dynamics of the actual phase jitter model is unknown. Several specific state estimation formulations are discussed in detail from this point of view. Among the nonlinear observation models considered are those associated with a constant phase offset, a linear phase model and a piece-wise linearity in the phase jitter. Also, attempt has been made to compare the performance of the state estimation techniques with that of the conventional fixed gain phase-locked loops.

Experience with Guidelines for Software Projects of Public Administration

Abstract In the public administration of the Federal Republic of Germany planning and realization of software projects for the automation of administrative processes are orientated on a linear phase model (’waterfall model’). In the paper the guidelines of the committee for cooperation for automated data processing at federal /state/communal level are explained, especially the basic idea for the limitation of the single phases. This prescribed procedure has increasingly to be taken into critical consideration on the basis of practical experience in the management of complex software projects. The ineffectiveness of the planned checkpoints and characteristic tendencies in finding of requested solutions will be comprehensively explained. Initiated by such negative effects, an alternative procedure for complex projects of automated administration will be presented. These are based on a holistic development of a network of relatively autonomous sub-units. The realization of the imprecise expressed ideals will be carried out within the framework of a working hypothesis: learning system, the centre of which is prototyping.

Modeling acoustic attenuation of soft tissue with a minimum-phase filter.

Soft biological tissue has been observed to exhibit an acoustic attenuation log-magnitude characteristic which increases as an approximately linear function of frequency. This paper describes the implementation of a finite-impulse-response (FIR) digital filter model for simulating this behavior on a digital computer. To insure that the filter is causal, the minimum-phase constraint is imposed. For minimum-phase filters, the log-magnitude and phase characteristics form a Hilbert Transform pair. The discrete-time Hilbert Transform of the linear log-magnitude characteristic was evaluated to determine the phase of the filter. The inverse Fourier Transform of the resulting real and imaginary components of the frequency transform produces the finite-duration unit-sample response of the digital filter model. Experimental results using plexiglas material, which has a linear-with-frequency loss characteristic, indicate that the minimum-phase model is more accurate than the linear-phase model, resulting in a rms error between predicted and observed time waveforms that is 3 times smaller. The effects of varying the sampling period and the size of the FIR filter are discussed. A FORTRAN program to calculate the minimum-phase unit-sample response from the slope of the log-magnitude characteristic is included in the Appendix.

Modeling acoustic attenuation of soft tissue with a minimum-phase filter

Soft biological tissue has been observed to exhibit an acoustic attenuation log-magnitude characteristic which increases as an approximately linear function of frequency. This paper describes the implementation of a finite-impulse-response (FIR) digital filter model for simulating this behavior on a digital computer. To inaure that the filter is causal, the minimum-phase conatraint is imposed. For minimum-phase filters, the log-magnitude and phase characteristics form a Hilbert Transform pair. The discrete-time Hilbert Transform of the linear logmagnitude characteristic was evaluated to determine the phase of the filter. The inverse Fonrier Transform of the resulting real and imaginary components of the frequency transform produces the finite-duration unitsample response of the digital filter model. Experimental results using plexiglas material, which has a linear-with-frequency loss characteristic, indicate that the minimum-phase model is more accurate than the linear-phase model, resulting in a rms error between predicted and observed time waveforms that is 3 times maller. The effects of varying the sampling period and the size of the FIR filter are discussed. A FORTRAN program to calculate the minimum-phase unit-sample response from the slope of the logmagnitude characteristic is included in the Appendix.

Digital filter models for media having linear with frequency loss characteristics

Linear with frequency acoustic loss characteristics have been observed for soft biological tissue when probed with diagnostic ultrasound and for Plexiglas when used for underwater applications. Two digital filter models are described that exhibit this linear characteristic. The first filter model, designed using a frequency sampling technique, produces a symmetric unit sample response and a linear with frequency phase characteristic. Several features of this linear phase model, however, are found to be incompatible with the physical mechanisms producing the loss. Upon resolving these incompatibilities, a second filter model is obtained which has a minimum phase transfer function. Experimental verification, using Plexiglas as an acoustic propagation medium, demonstrates the superiority of the minimum phase model for describing the physical mechanisms which produce a linear with frequency loss characteristic.