A control-theoretic approach for efficient design of filters in DAC and digital audio amplifiers

A control-theoretic approach in designing Digital-to-Analogue Converters and Digital Amplifiers which leads to improved performance in Audio and Multimedia applications is presented in this paper. The design involves an over-sampling and a pulse modulation component which is driven by a pulse generation algorithm based on the characteristics of the output filter. The theoretical model results in a family of digital circuits whose operation is verified by computer simulations achieving a performance of Signal-to-Noise Ratio of 147 dB at a switching rate of 90 MHz. Implementation and hardware complexity issues are discussed based on a FPGA realization of the algorithm. © 2010 Springer Science+Business Media, LLC

Autoregressive Modeling and Feature Analysis of DNA Sequences

<p/> <p>A parametric signal processing approach for DNA sequence analysis based on autoregressive (AR) modeling is presented. AR model residual errors and AR model parameters are used as features. The AR residual error analysis indicate a high specificity of coding DNA sequences, while AR feature-based analysis helps distinguish between coding and noncoding DNA sequences. An AR model-based string searching algorithm is also proposed. The effect of several types of numerical mapping rules in th proposed method is demonstrated.</p

Towards real-time neuronal connectivity assessment: A scalable pipelined parallel generalized partial directed coherence engine

The current paper introduces a real-time architecture for the computation of the Generalized Partial Directed Coherence (GPDC) of multiple signals. The motivating application is the localization and control of epileptic seizures where hitherto published results shown the effectiveness of exploiting Generalized Partial Directed Coherence to quantify and analyse connectivity and interaction of brain structures. To speed up GPDC computations we develop first, a parallelizing strategy leading to the high performance scalable architecture and second, a low-complexity fixed-point reciprocal square root module. We show that a real-time computation is feasible at a speed of 0.027ms for 16 channels and 1.637ms for 128 channels. Furthermore, the implementation results on Xilinx 7A35T, KC705, VC707, KU115 show that the power requirements are quite modest and allow for the embedded application of the engine

Brain dynamical disentrainment by anti-epileptic drugs in rat and human status epilepticus

In this paper, we utilize a measure of brain dynamics, namely the short-term largest Lyapunov exponent (STLmax) to evaluate the efficacy of treatment in epileptic animals and humans with known antiepileptic drugs (AED) like diazepam and phenobarbital during status epilepticus (SE). This measure is estimated from analysis of electroencephalographic (EEG) recordings at multiple brain locations in both an SE patient and a cobalt/homocysteine thiolactone SE-induced animal. Techniques from optimization theory and statistics are applied to select optimal sets of brain sites, whose dynamics are then measured over time to study their entrainment/disentrainment. Results from such analysis indicate that the observed abnormal spatio-temporal dynamical entrainment in SE is reversed by AED administration (resetting of brain dynamics). These results may provide a potential use of nonlinear dynamical measures in the evaluation of the efficacy of AEDs and the development of new treatment strategies in epilepsy

Brain dynamics based automated epileptic seizure detection

We developed and tested a seizure detection algorithm based on two measures of nonlinear and linear dynamics, that is, the adaptive short-term maximum Lyapunov exponent (ASTLmax) and the adaptive Teager energy (ATE). The algorithm was tested on long-term (0.5-11.7 days) continuous EEG recordings from five patients (3 with intracranial and 2 with scalp EEG) with a total of 56 seizures, producing a mean sensitivity of 91% and mean specificity of 0.14 false positives per hour. The developed seizure detection algorithm is data-adaptive, training-free, and patient-independent

Mitral-Aortic intervalvular fibrosa pseudoaneurysm

Pseudoaneurysm of the mitral aortic intervalvular fibrosa (MAIVF-P) usually ensues as a complication of endocarditis or aortic valve surgery. When large, symptomatic or related to complications (rupture, compression of adjacent structures, embolic events, mitral regurgitation or heart failure) it warrants surgical excision. The natural course of uncomplicated/asymptomatic MAIVF-Ps is largely unknown since most patients are offered surgery. Increased surgical risk imposed by repeat operations in the majority of these patients is an important consideration and conservative treatment should not be excluded in selected cases. Herein we present two illustrative cases of MAIVF-P manifesting with significant arrhythmogenesis and complex endocarditis respectively. Both patients were managed conservatively. By briefly reviewing the existing literature, we discuss important diagnostic and therapeutic issues for MAIVF-Ps. To our knowledge complex ventricular arrhythmia has not been previously described as a prominent manifestation of MAIVF-P. © 2015 Korean Society of Echocardiography