Results on optimal biorthogonal filter banks

Optimization of filter banks for specific input statistics has been of interest in the theory and practice of subband coding. For the case of orthonormal filter banks with infinite order and uniform decimation, the problem has been completely solved in recent years. For the case of biorthogonal filter banks, significant progress has been made recently, although a number of issues still remain to be addressed. In this paper we briefly review the orthonormal case, and then present several new results for the biorthogonal case. All discussions pertain to the infinite order (ideal filter) case. The current status of research as well as some of the unsolved problems are described

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Optimal orthonormal subband coding and lattice quantization with vector dithering

In the digital era that we live in, efficient coding of signals is an unquestionable need. This thesis is about one of the most useful and popular technique of digital coding: subband coding. Subband coding and its cousin wavelet-based coding are now the preferred methods for not only speech, but also audio, image, and video signals. Subband coding involves a linear part which is a filter bank, and a nonlinear part which is usually a uniform scalar quantization of each of the subbands. Subband coders are classified according to the type of filter bank used for its transform. This thesis is mainly about orthonormal subband coding. The ability of an orthonormal filter bank to decompose the signal into components that have a diverse set of signal energies is an indicator of its efficiency for subband coding. Such a diversity in the set of the subband energies is fully utilized by a process called bit allocation. The traditional results on the optimality of a filter bank for given input statistics assume that the quantizers operate at high bit rates. This thesis presents optimality results under more general quantizer models without assuming high bit rates. This is accomplished by revealing the relationship between the problems of optimal orthonormal subband coding and principal component representation of signals. The latter is done using what is called a principal component filter bank (PCFB). A PCFB is one that compacts most of the energy of a signal into smaller subsets of subbands. To date, there has not been significant theoretical developments in the field of optimal nonuniform subband coding, although the successful techniques of wavelet-based coding are among the state of the art in practice. Such techniques utilize a form of a nonuniform filter bank with a certain structure which makes it efficient for its implementation. In this thesis, we provide optimality results for the nonuniform orthonormal subband coding as well. As in the uniform case, the principal component representation of signals continues to play the key role. We introduce nonuniform PCFB's and link them to the optimal subband coding problem. A PCFB, in particular, contains a filter that compacts most of the signal energy into one single channel: energy compaction filter. The thesis goes into details of designing such filters optimally. In particular, we propose an analytical method in the two-channel case and a very efficient window method in the arbitrary M—channel case. Multistage design of compaction filters has also been worked out. Finally we extend the analysis of uniform scalar quantization to multiple dimensions. We provide an exact statistical relationship between a lattice quantizer noise and its input vector. We then extend the idea of dithering to the vector case. Dithering is a means of statistically rendering the quantization noise independent of the input. We address the optimal choice of a lattice for a given dimension and also optimal pre- and post-filtering of a dithered lattice quantizer

Theory And Design Of Optimum FIR Compaction Filters

The problem of optimum FIR energy compaction filter design for a given number of channels M and a filter order N is considered. The special cases where N ! M and N = 1 have analytical solutions that involve eigenvector decomposition of the autocorrelation matrix and the power spectrum matrix respectively. In this paper, we deal with the more difficult case of M ! N ! 1. For the two-channel case and for a restricted but important class of random processes, we give an analytical solution for the compaction filter which is characterized by its zeros on the unit-circle. This also corresponds to the optimal two-channel FIR filter bank that maximizes the coding gain under the traditional quantization noise assumptions. This can also be used to generate optimal wavelets. For the arbitrary M \Gammachannel case, we provide a very efficient suboptimal design method called the window method. The method involves two stages that are associated with the above two special cases. As the order incre..

Fir Compaction Filters: New Design Methods And Properties

Energy compaction has proven to be an essential concept in signal-adapted data compression. In particular, optimization of orthonormal subband coders for a given power spectrum directly leads to optimal energy compaction filters. In this paper, we consider some new design methods and properties of optimal FIR energy compaction filters. In particular, we propose a very efficient method called the window method for the general M-channel case. The method does not involve any sophisticated optimization tools and terminates in a finite number of elementary steps. Compaction gains achieved by the method are very close to the optimal ones. As the filter order increases the filters of the proposed method converge to the optimum ideal compaction filters. 1. INTRODUCTION The energy compaction problem has recently attracted considerable attention. It is shown that optimal orthonormal (paraunitary, PU) filter banks that maximize coding gain consist of optimal energy compaction filters [2, 8, 9, 1..

Efficient Design Methods of Optimal FIR Compaction Filters for M-channel FIR Subband Coders

We propose algorithms for the design of FIR compaction filters, which find applications in FIR subband coders. The techniques produce compaction gains very close to that of optimal compaction filters, for any fixed filter order and input autocorrelation. The main theme of the paper is the design of multistage FIR compaction filters based on an iterated linear programming approach. The theory behind this is presented followed by design examples and comparisons. Also, a noniterative algorithm much faster than other iterative optimization techniques (e.g. linear programming) will be briefly mentioned. Further details of noniterative techniques will be presented elsewhere. 1 Introduction We will describe some efficient methods to design FIR compaction filters. These filters find application in M \Gammachannel FIR orthonormal filter banks [11]. Because of this basic application, we will refer to "M \Gammachannel compaction filters", although there will be only one filter to work with. Th..

Prognostic nutritional index as indicator of immune nutritional status of patients with COVID-19

Purpose: This study aimed to investigate the effect of the nutritional status, as assessed by the prognostic nutritional index (PNI) on the disease prognosis of patients with COVID-19. Methods: This retrospective study included 282 patients with COVID-19. The PNI score of all patients, 147 of whom were male, with a mean age of 56.4 +/- 15.3 years, was calculated. According to the PNI score, the patients with normal and mild malnutrition constituted group-1 (n=159) and the patients with moderate-to-severe and serious malnutrition constituted group-2 (n=123). Results: The PNI score was correlated with age (r=-0.146, p=0.014); oxygen saturation (r=0.190, p=0.001); heart rate (r=-0.117, p=0.05); hospitalization duration (r=-0.266, p= 65 years score (r=-0.217, p41.2 (p<0.001, sensitivity: 78.7% and specificity: 84.2%). In multivariate regression analysis, among various other parameters, only PNI score and oxygen saturation had a significant effect on the disease course (p=0.02 and p=0.045, respectively). Conclusion: PNI, calculated from the serum albumin concentration and total lymphocyte count, is a simple and objective indicator that assesses the immune nutritional status of patients with COVID-19. The presence of malnutrition has a high predictive value in predicting the severity of COVID-19. Our data suggest that the PNI might be useful for risk stratification of patients with COVID-19 in clinical practice

Analysis of heart rate variability and risk factors for SUDEP in patients with drug-resistant epilepsy

Background: Cardiac problems have been suggested as causes of sudden unexpected death in epilepsy (SUDEP). Our aim was to investigate possible associations of cardiac autonomic functions based on heart rate variability (HRV) parameters with risk factors of SUDEP in patients with drug-resistant epilepsy