Sharif Digital Repository

Among the many attacks against watermarked data, the gain attack is less supported with countermeasures. The effectiveness of this attack becomes more evident in quantization-based embedding algorithms such as Dither Modulation (DM). In this paper, the general solution for both block and sample type DM schemes that are robust against gain attacks is considered. Among the solutions, we concentrate on a subclass of the algorithms which are insensitive to additive noise attacks; i.e., we introduce watermarking schemes which are both robust against gain and additive noise attacks. The simulation results confirm the desired performance of the final algorithm against these attacks while outperform... 

A new fast and very accurate method for target detection in PCL radars is presented. This algorithm in noisy environment with SNR up to -60dB could provide the perfect and accurate detection. Presented initiative algorithm apply a special filter bank to the target signal and clean the additive noise of the environment from it and detect the multiple targets with different RCSs. © 2006 EuMA  

An Artificial Neural Network (ANN) based helicopter identification system is proposed. All helicopters emit certain characteristic acoustic signatures, which are specific to them. This is due to some differences in their structures and design. These differences in acoustic signatures can be used with neural networks for detection and classification of different types of helicopters. The conventional system uses the ratio of the main-rotor blade passage frequency (bpf) to the tail-rotor bpf. The ANN is trained to use similar main/tail-rotor information, in addition to the parametric spectral representation technique (Reflection Coefficients). It is also shown that the classifier performance... 

In this paper, the detection of a coded signal in additive white Gaussian noise and the interference is studied, where there is no knowledge about the correlation between the received symbols and about the noise and interference parameters. The Maximum Likelihood (ML) estimates of the unknown parameters are found, they are substituted in the probability density functions of the observation and the Generalized Likelihood Ratio (GLR) detector is derived. This detector can also be used for the activity detection of a signal in unknown Inter-Symbol Interference (ISI). In this case, the interference is modeled as the unknown correlation between the received symbols. Simulation examples are... 

In this paper, a class of uncertain piecewise affine (PWA) systems, subject to system and measurement additive noises is studied. The additive noise signals considered here do not vanish at the equilibrium and the uncertainties are norm bounded. The problem of minimizing the bound on the variance of the steady response of uncertain PWA systems, by means of a hybrid observer-controller, is formulated as an optimization problem subject to a number of constraints in the form of matrix inequalities. The derived constraints are obtained by considering a piecewise quadratic Lyapunov function in combination with the general stability conditions regarding the existence of an upper stochastic bound... 

We propose two nonlinear regression methods, namely, Adversarial Orthogonal Regression (AdOR) for additive noise models and Adversarial Orthogonal Structural Equation Model (AdOSE) for the general case of structural equation models. Both methods try to make the residual of regression independent from regressors, while putting no assumption on noise distribution. In both methods, two adversarial networks are trained simultaneously where a regression network outputs predictions and a loss network that estimates mutual information (in AdOR) and KL-divergence (in AdOSE). These methods can be formulated as a minimax two-player game; at equilibrium, AdOR finds a deterministic map between inputs... 

Noise reduction of speech signals plays an important role in telecommunication systems. Various types of speech additive noise can be introduced such as babble, crowd, large city, and highway which are the main factor of degradation in perceived speech quality. There are some cases on the receiver side of telecommunication systems, where the direct value of interfering noise is not available and there is just access to noisy speech. In these cases the noise cannot be cancelled totally but it may be possible to reduce the noise in a sensible way by utilizing the statistics of the noise and speech signal. In this paper the proposed method for noise reduction is Bayesian recursive state-space... 

In speech production systems, the vocal tract is modeled by a filter and glottal pulse by an excitation signal. In most traditional systems impulse train or noise is used as the excitation. In this paper the effects of different excitation signals on Mel-generalized cepstral filters (LPC, warped LPC, mel cepstral and ML cepstral) are studied. Excitation signals with different pulse shapes are used. Furthermore, based on voicing power, noise factor is added to the excitation signals. Totally 600 different experiments with different filter types, number of coefficients, pulse shapes, pulse widths and noise power are preformed. Synthesized speech is evaluated by PESQ measure. A number of pulse... 

We propose a new inverse scattering technique based on sparsity for the application of microwave imaging. The underdetermined inverse problem appeared in the distorted born iterative method (DBIM) technique is solved using the suggested L2-regularized iterative weighted algorithm (L2-IWA). The L2-regularizer has been introduced to stabilize the algorithm against nonlinear approximations, and the sparsity is enforced with the aid of another reweighted L2-norm regularizer to address the ill-posedness of the inverse problem. The derived algorithm is a three-step iterative technique which solves the underdetermined set of equations at each DBIM iteration. Moreover, the convergence of the L2-IWA... 

In this paper a sub-optimal control technique is proposed for a linear Gaussian system with a few distributed interacting sub-systems. Controller of each sub-system has only access to its own measurement and a noisy version of measurement and control vectors of other sub-systems that are communicated through an Additive White Gaussian Noise (AWGN) communication network. The power to be allocated to each transmitter antenna is calculated so that the received signal is the transmitted signal plus additive white Gaussian noise. Under some conditions it is shown that the proposed sub-optimal control technique results in bounded mean square stability. The satisfactory performance of the proposed... 

In this paper, the impact of a small variations in the channel gains on the secrecy rate of the wiretap channel is studied, in which it is assumed that the imperfect channel knowledge is available at the transmitter. First, we consider general additive noise model for both legitimate and eavesdropper channels in the wiretap channel, and compute the variation of the secrecy rate resulting from the small variations in the channel gains. Then, we focus on the Gaussian wiretap channel, as a special case and calculate the sensitivity of the secrecy capacity to the channel gains with imperfect channel knowledge. Interestingly, it is shown that in some situations the effect of the channel variation... 

This paper deals with identification of discrete-time errors-in-variables models where the input and output data are both perturbed by different additive noises. The goal is to study the effects of input noise on the model which is estimated based on the prediction error method. The obtained model is then improved by modifying the results and implementing the instrumental variable method. It is proved that the identification of the errors-in-variables models based on the proposed approach could result in an unbiased estimation in the presence of independent colour noises on the input and output data with adequate accuracy and mediocre complexity. © 2017 Informa UK Limited, trading as Taylor... 

This paper deals with identification of discrete-time errors-in-variables models where the input and output data are both perturbed by different additive noises. The goal is to study the effects of input noise on the model which is estimated based on the prediction error method. The obtained model is then improved by modifying the results and implementing the instrumental variable method. It is proved that the identification of the errors-in-variables models based on the proposed approach could result in an unbiased estimation in the presence of independent colour noises on the input and output data with adequate accuracy and mediocre complexity. © 2017, © 2017 Informa UK Limited, trading as... 

The interferometer method as one of the most accurate schemes for wideband direction finding (DF) is used. The interferometer method has various algorithms which can be implemented depending on the required specifications. The advantages and disadvantages of these algorithms have been evaluated and the appropriate algorithm for a general practical case in view of the ambiguity resolution is proposed. The receivers’ channel phase tracking error is of significant concern in practice in interferometric DF systems. The induced error due to channels phase tracking error is estimated. Furthermore the use of physically realizable antennas, achievement of high accuracy, minimum number of antennas... 

In this paper, we obtain a family of lower bounds for the sum capacity of code-division multiple-access (CDMA) channels assuming binary inputs and binary signature codes in the presence of additive noise with an arbitrary distribution. The envelope of this family gives a relatively tight lower bound in terms of the number of users, spreading gain, and the noise distribution. The derivation methods for the noiseless and the noisy channels are different but when the noise variance goes to zero, the noisy channel bound approaches the noiseless case. The behavior of the lower bound shows that for small noise power, the number of users can be much more than the spreading gain without any... 

In this paper, a new algorithm for source recovery in under-determined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented in the noisy case. The algorithm is essentially a method for obtaining sufficiently sparse solutions of under-determined systems of linear equations with additive Gaussian noise. The method is based on iterative Expectation-Maximization of a Maximum A Posteriori estimation of sources (EM-MAP) and a new steepest-descent method is introduced for the optimization in the Mstep. The solution obtained by the proposed algorithm is compared to the minimum ℓ1-norm solution achieved by Linear Programming (LP). It is experimentally... 

In this article, a novel cooperative secondary voltage/frequency control considering time-varying delays and noises in fading channels is presented for an autonomous alternating current (AC) voltage sourced-based converter (VSC)-based microgrid (MG), including inverter-interfaced distributed generations (DGs). Fading phenomenon makes complex random fluctuations on the voltage and frequency of every DG received from its neighbor DGs. In multi-agent cooperative systems, in addition to the total additive noise and time-variant delay, a multiplicative complex random variable is considered to model the main received signal and its replicas due to multipath propagation. The proposed... 

A coding scheme for transmission of a bit maps a given bit to a sequence of channel inputs (called the codeword associated with the transmitted bit). In this paper, we study the problem of designing the best code for a discrete Poisson channel with memory (under peak-power and total-power constraints). The outputs of a discrete Poisson channel with memory are Poisson distributed random variables with a mean comprising of a fixed additive noise and a linear combination of past input symbols. Assuming a maximum-likelihood (ML) decoder, we search for a codebook that has the smallest possible error probability. This problem is challenging because error probability of a code does not have a... 

A coding scheme for transmission of a bit maps a given bit to a sequence of channel inputs (called the codeword associated to the transmitted bit). In this paper, we study the problem of designing the best code for a discrete Poisson channel with memory (under peak-power and total-power constraints). The outputs of a discrete Poisson channel with memory are Poisson distributed random variables with a mean comprising a fixed additive noise and a linear combination of past input symbols. Assuming a maximum-likelihood (ML) decoder, we find the best codebook design by minimizing the error probability of the decoder over all codebooks. For the case of having only a total-power constraint, the... 

A coding scheme for transmission of a bit maps a given bit to a sequence of channel inputs (called the codeword associated with the transmitted bit). In this paper, we study the problem of designing the best code for a discrete Poisson channel with memory (under peak-power and total-power constraints). The outputs of a discrete Poisson channel with memory are Poisson distributed random variables with a mean comprising of a fixed additive noise and a linear combination of past input symbols. Assuming a maximum-likelihood (ML) decoder, we search for a codebook that has the smallest possible error probability. This problem is challenging because error probability of a code does not have a...