A novel Multiple Input Single Output (MISO) universal biquad filter topology realized using Current Feedback Operational Amplifiers (CFOAs) is introduced in this paper. With regards to the corresponding already published MISO universal biquads with CFOAs, the proposed topology simultaneously offers the benefits of employing only grounded capacitors, absence of any imposed constraint related to the values of input signals, and orthogonal adjustment between the quality factor and resonant frequency of the filter. The operation of the proposed biquad has been verified through experimental results by utilizing the commercially available AD844 CFOA discrete component.

We consider a singularly perturbed system of differential equations of the form eu′=g(u,v,λ), v′=f(u,v,λ), where (u,v)∈R3, 0<e≪1, and λ is a set of parameters. Such a system describes a modified Chua’s circuit with mixed-mode oscillations (MMOs). MMOs consist of a series of small-amplitude oscillations (canard solutions) and large-amplitude relaxations. In the paper we provide a series of both numerical and analytical analyses of the singularly perturbed system for the modified Chua’s circuit with nonlinear f and g. In particular, we analyze the occurrence of the Farey sequence\(\it L^{s}\), where \(\it L\) and \(\it s\) are the numbers of large and small oscillations, respectively.

A frequently encountered problem in signal processing is harmonic retrieval in additive colored Gaussian or non-Gaussian noise, especially when the frequencies of the harmonic signals are very close in space. The purpose of this paper is to develop an efficient Blind Source Separation (BSS) algorithm from linear mixtures of source signals, which enables to separate harmonic source signals using only one observed channel signal even if the frequencies of the harmonic signals are closely spaced. First, we establish the BSS based harmonic retrieval model in additive noise by using the only one observed channel, and analyze the fundamental principle by utilizing BSS method to retrieve harmonics. Then, we propose a BSS-based approach to the harmonic retrieval by resorting the concept of W-disjoint orthogonality in the over-complete BSS situation, and as a result, we get the separation algorithm using only one channel mixed signals. Simulation results show that the proposed separation algorithm-BSS-HR is able to separate the harmonic source signals.

This paper is concerned with the gain-scheduled H∞ filtering problem for a class of parameter-varying continuous systems with time delays. The systems under consideration are represented by nonlinear fractional transformation (NFT) which is a generalization of linear fractional transformation (LFT). Attention is focused on the design of a stable filter guaranteeing a prescribed disturbance attenuation level in an H∞ sense. Sufficient solvability conditions of this problem are obtained based on Lyapunov function approach. A gain-scheduled filter can be constructed in terms of a set of linear matrix inequalities (LMIs). A numerical example is provided to demonstrate the applicability of the proposed approach.

This paper discusses the problem of robust delay-dependent exponential stability for a class of uncertain stochastic systems with time-varying delay. The uncertainty is assumed to be of norm-bounded form. A less conservative robust exponential stability condition is derived by using a new Lyapunov–Krasovskii functional and a free-weighting matrix method in terms of linear matrix inequalities. Two numerical examples are given to illustrate the effectiveness of the proposed method.

The proposed architecture features an independent setting of filter poles, while ensuring a constant unity gain. The unity gain simplifies the cascaded connection of filter blocks and avoids the increase of voltage swing for subsequent cascaded blocks observed with other filter architectures. Only the input Operational Amplifier must meet more demanding requirements (in terms of bandwidth and open-loop gain), while the other units are voltage follower units with the possibility of using a video buffer to cope with a demanding load capability. Performances are much better than or comparable to other known filter architectures.

This work pertains to the use of superimposed training (ST) for channel estimation in orthogonal frequency division multiplexing (OFDM) based systems. A time domain coherent averaging based channel estimator is derived from the least squares criterion. By exploiting the periodicity of the training sequences in the time domain and inserting zeros instead of data at some of the training sequence subcarrier locations depending on the desired estimation accuracy, a controlled superimposition technique is proposed. This method includes the flexibility to trade off between bandwidth efficiency and performance. The mean squared estimation error (MSEE) performance of such a system is mathematically analyzed and a training sequence selection criterion optimizing the same is proposed. The simulation performance of the scheme is presented in terms of the MSEE and the bit error rate (BER) of the OFDM system. Such a scheme is attractive in high data rate scenarios in closed loop OFDM systems.

This paper deals with the problem of joint frequency offset (FO) and channel estimation for multi-input multi-output (MIMO) systems in the presence of a timing error. Two equivalent signal models with FO and a timing error are given, and then a joint estimation method is derived. The proposed estimation method consists of two steps. Firstly, a maximum likelihood (ML) FO estimator is proposed based on the second signal model. Secondly, based on the FO estimate, we formulate the timing error and channel estimation as a problem of composite hypothesis testing according to the first signal model, and then solve the problem using a composite hypothesis testing approach. Simulation results are performed to show the effectiveness of the proposed method.

In this paper two new voltage-mode (VM) universal filters employing three plus-type differential voltage current conveyors (DVCC+s) and grounded passive elements are presented. The first proposed filter is a single-input five-output (SIFO) circuit which can realize simultaneously all of the standard responses, i.e. low-pass (LP), band-pass (BP), high-pass (HP), all-pass (AP) and notch (NH) from the same configuration. The second proposed circuit is a three-input single-output (TISO) universal filter for realizing standard responses depending on the selection of the input signal from the same topology. Both of the proposed filters have the advantage of a high input impedance, which enables easy cascading to obtain higher order filters. The proposed filters are simulated using the SPICE program to verify the theoretical analysis.

In this paper, we present an approach to incorporate discriminative weight training into a statistical model-based voice activity detection (VAD) method. In our approach, the VAD decision rule is derived from the optimally weighted likelihood ratios (LRs) using a minimum classification error (MCE) method. An adaptive on-line means of selecting two kinds of weights based on a power spectral flatness measure (PSFM) is devised for performance improvement. The proposed approach is compared to conventional schemes under various noise conditions, and shows better performance.