an adaptive receiver for the time and frequency selective fading channel an adaptive receiver is presented in this paper for the reception of linearly modulated signals transmitted over a time and frequency selective fading channel the channel is modeled as a truncated power series which represents the dispersive fading channel as a sum of three elementary flat fading channels the proposed receiver consists of a sequence estimator with a parallel channel estimator the channel estimator recovers the instantaneous fading processes associated with each elementary channel and filters them to generate one step predictions of each fading process some implementation difficulties and solutions are also discussed computer simulations using quadrature phase shift keying qpsk and channels with moderate delay spreads and fade rates have been used to evaluate the performance of the receiver the results show that our technique has potential in channels with delay spread of about 20 signal to noise ratio snr greater than 15 db and applications requiring bit error rates ber s less than 10 sup 2

energy decay rate of wave equations with indefinite damping abstract we consider the one dimensional wave equation with an indefinite sign damping and a zero order potential term using a shooting method we establish the asymptotic expansion of eigenvalues and eigenvectors of the damped wave equation for a large class of coefficients in addition if the damping coefficient is more positive than negative we prove that the energy of system decays uniformly exponentially to zero this sharp result generalizes a previous work of freitas and zuazua 1996

statistics of a neuron model driven by asymmetric colored noise irregular firing of neurons can be modeled as a stochastic process here we study the perfect integrate and fire neuron driven by dichotomous noise a markovian process that jumps between two states i e possesses a non gaussian statistics and exhibits nonvanishing temporal correlations i e represents a colored noise specifically we consider asymmetric dichotomous noise with two different transition rates using a first passage time formulation we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval time interval between two subsequent neural action potentials and the power spectrum of the spike train furthermore we extend the model by including additional gaussian white noise and we give approximations for the interspike interval isi statistics in this case numerical simulations are used to validate the exact analytical results for pure dichotomous noise and to test the approximations of the isi statistics when gaussian white noise is included the results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics

exponential decay of energy of evolution equations with locally distributed damping consider an evolution equation with energy dissipation frac partial partial t y x t ay x t by x t on a bounded x domain omega where by signifies a dissipative perturbation to an otherwise energy conserving system this dissipation may be due to medium impurities viscous effects or artificially imposed dampers and stabilizers it is distributed over only part of the domain omega the question of when the dissipation is effective enough to cause uniform exponential decay of energy is examined because of the locally distributed nature of energy dissipation the problem lacks coercivity and is not directly solvable by energy identities thus to get conditions sufficient for uniform exponential decay a different approach needs to be taken provided here is a set of tight sufficient conditions in terms of the influence of the dissipative operatorbon the separated eigenmodes or clustered eigenmodes ofa the main theorems are general enough to treat the wave and bea

statistics of a leaky integrate and fire model of neurons driven by dichotomous noise the behavior of a stochastic leaky integrate and fire model of neurons is considered the effect of temporally correlated random neuronal input is modeled as a colored two level dichotomous markovian noise relying on the riemann method exact expressions for the output interspike interval density and for the serial correlation coefficient are derived and their dependence on noise parameters such as correlation time and amplitude is analyzed particularly noise induced sign reversal and a resonancelike amplification of the kurtosis of the interspike interval distribution are established the features of spike statistics analytically revealed in our study are compared with recently obtained results for a perfect integrate and fire neuron model

bresse system with indefinite damping abstract we consider the bresse system in a bounded domain 0 l r 1 the system has an indefinite damping mechanism i e with a damping function a a x possibly changing sign presented only in the equation for the rotation angle we shall prove that the system is still exponentially stable under the same conditions as in the positive constant damping case and provided a 1 l 0 l a x d x 0 and a a l 2 for small enough in the arguments we shall also give a new proof of exponential stability for the constant case a a

effects of transient subordinators on the firing statistics of a neuron model driven by dichotomous noise the behavior of a stochastic perfect integrate and fire pif model of neurons is considered the effect of temporally correlated random activity of synaptic inputs is modeled as a combination of an asymmetric dichotomous noise and a random operation time in the form of an inverse strictly increasing levy type subordinator using a first passage time formulation we find exact expressions for the output interspike interval isi statistics particularly it is shown that at some parameter regimes the isi density exhibits a multimodal structure moreover it is demonstrated that the coefficient of variation the serial correlation coefficient and the fano factor display a nonmonotonic dependence on the mean input current i e the isi s regularity is maximized at an intermediate value of the features of spike statistics analytically revealed in our study are compared with previously obtained results for a perfect integrate and fire neuron model driven by dichotomous noise without subordination

bimodality of the interspike interval distributions for subordinated diffusion models of integrate and fire neurons abstract a subordinated langevin process with a random operational time in the form of an inverse strictly increasing levy type subordinator is considered as a generalization of the conventional perfect and leaky integrate and fire neuron models the parent process is given by standard brownian motion the effect of the random activity of synaptic inputs which arises from other neurons forming local and distant networks is modeled via a levy exponent of the subordinator using a first passage time formulation in an external force field we find exact expressions for the laplace transform of the output interspike interval isi density more detailed analysis is presented on the properties of the isi distribution in the case of the levy exponent which corresponds to the truncated double order time fractional diffusion equation for the probability density of the membrane potential particularly it is shown that at some parameter regimes the isi density exhibits a bimodal structure moreover it is demonstrated that the isis regularity is maximized at an intermediate value of the mean input current

timoshenko systems with indefinite damping abstract we consider the timoshenko system in a bounded domain 0 l r 1 the system has an indefinite damping mechanism i e with a damping function a a x possibly changing sign present only in the equation for the rotation angle we shall prove that the system is still exponentially stable under the same conditions as in the positive constant damping case and provided a 0 l a x d x 0 and a a l 2 for small enough the decay rate will be described explicitly in the arguments we shall also give a new proof of exponential stability for the constant case a a moreover we give a precise description of the decay rate and demonstrate that the system has the spectrum determined growth sdg property i e the type of the induced semigroup coincides with the spectral bound for its generator

stabilization of the wave equations with potential and indefinite damping by means of global carleman type estimate we study the stabilization problem of the wave equations with potential and indefinite damping the energy decay rate of the system is given explicitly also we obtain an upper bound estimate on the negative damping to guarantee the energy of the system decays exponentially

exponential stability of wave equations with potential and indefinite damping abstract first we consider the linear wave equation u t t u x x a x u t b x u 0 on a bounded interval 0 l r the damping function a is allowed to change its sign if a 1 l 0 l a x d x is positive and the spectrum of the operator x x b is negative exponential stability is proved for small a a l 2 explicit estimates of the decay rate are given in terms of a and the largest eigenvalue of x x b second we show the existence of a global small smooth solution of the corresponding nonlinear wave equation u t t u x x a x u t b x u 0 if additionally the negative part of a is small enough compared with

asymptotic stability for bresse systems abstract in this paper consider a vibrating system of bresse type in a one dimensional bounded domain with a nonlinear damping acting in the equation of the shear angle displacement and nonlinear localized damping in other equations we show the asymptotic stability without imposing conditions about the equal speed wave propagation using a method developed by lasiecka and tataru 9

maximum likelihood sequence estimation of cpm signals transmitted over rayleigh flat fading channels a method for the sequential updating of log likelihood functions for maximum likelihood sequence estimation is presented it is shown that in a general case this method can be implemented using kalman filtering techniques for the special case of rayleigh flat fading and continuous phase modulation cpm signaling this approach is shown to lead to an attractive receiver structure this type of receiver called the linear predictive receiver can be implemented in the form of the viterbi algorithm with the trellis updates being computed using a bank of finite pulse response fir filter and square operations simulation results are presented that demonstrate the superiority of the linear predictive receiver over receivers employing differential detection in the presence of fast fading it is shown that the optimal linear predictive receiver does not possess an irreducible error rate for a class of rayleigh fading channels used to model terrestrial mobile channels

isometric data sequences and data modulation schemes in fading channels in multiplicative fading channels joint channel estimation and data detection ce dd schemes cannot differentiate among certain sequences of amplitude and or phase modulated am pm symbols drawn from rotationally invariant signal constellations this paper identifies these so called isometric sequences as the main source of performance degradation and introduces a unifying framework that effectively solves the problem by using asymmetric signal constellations asc and a normalized innovations based detector the encompassing nature of the solution is clearly demonstrated by showing that seemingly unrelated previous results such as training based solutions can be viewed as special cases of the modulation based solution discussed here a comprehensive analysis supported by simulation studies of the relationships among modulation schemes isometry and detection performance is provided results indicate that the proposed asc solution offers excellent performance without incurring significant complexity or reducing the transmission rate furthermore it is shown to be robust in various fading rates and for different signal constellations

stability to weak dissipative bresse system in this paper we study the bresse system with frictional dissipation working only on the angle displacement our main result is to prove that this dissipative mechanism is enough to stabilize exponentially the whole system provided the velocities of waves propagations are the same this result is significative only from the mathematical point of view since in practice the velocities of waves propagations are always different in that direction we show that when the velocities are not the same the system is not exponentially stable and we prove that the solution in this case goes to zero polynomially with rates that can be improved by taking more regular initial data finally we give some numerical result to verify our analytical results

stability results for the wave equation with indefinite damping abstract the one dimensional wave equation with damping of indefinite sign in a bounded interval with dirichlet boundary conditions is considered it is proved that solutions decay uniformly exponentially to zero provided the damping potential is in thebv class has positive average is small enough and satisfies a finite number of further constraints guaranteeing that the derivative of the real part of the eigenvalues is negative when the damping vanishes this sharp result completes a previous one by the first author showing that an indefinite sign damping always produces unstable solutions if it is large enough and it answers by the afirmative to a conjecture concerning small damping terms the method of proof relies on the developments by s cox and the second author on the high frequency asymptotic expansion of the spectrum for damped wave equations and on the characterization of the decay rate in terms of the spectral abscissa

exact results for power spectrum and susceptibility of a leaky integrate and fire neuron with two state noise this paper provides exact expressions for the power spectrum and the susceptibility of a leaky integrate and fire neuron driven by asymmetric two state noise the authors give an intuitive discussion of the undamped periodic oscillations resulting from their equations and also consider effects of additional broadband noise

interspike interval statistics of neurons driven by colored noise a perfect integrate and fire model driven by colored noise is studied by means of the interspike interval isi density and the serial correlation coefficient exact and approximate expressions for these functions are derived for weak dichotomous or gaussian noise respectively it is shown that correlations in the input result in positive correlations in the isi sequence and in a reduction of isi variability the results also indicate that for weak noise the noise distribution only shapes the isi density but not the isi correlations which are determined by the noise s correlation function