Performance Analysis of Wireless Systems with Doubly Selective Rayleigh Fading

Theoretical error performances of wireless communication systems suffering from both doubly selective (time varying and frequency selective) Rayleigh fading and sampler timing offset are analyzed in this paper. Single-input-single-output systems with doubly selective fading channels are equivalently represented as discrete-time single-input-multiple-output (SIMO) systems with correlated frequency-flat fading channels, with the correlation information being determined by the combined effects of sampler timing phase, maximum Doppler spread, and power delay profile of the physical fading. Based on the equivalent SIMO system representation, closed-form error-probability expressions are derived as tight lower bounds for linearly modulated systems with fractionally spaced equalizers. The information on the sampler timing offset and the statistical properties of the physical channel fading, along with the effects of the fractionally spaced equalizer, are incorporated in the error-probability expressions. Simulation results show that the new analytical results can accurately predict the error performances of maximum-likelihood sequence estimation and maximum a posteriori equalizers for practical wireless communication systems in a wide range of signal-to-noise ratio. Moreover, some interesting observations about receiver oversampling and system timing phase sensitivity are obtained based on the new analytical results

Output from VIP cells of the mammalian central clock regulates daily physiological rhythms

The suprachiasmatic nucleus (SCN) circadian clock is critical for optimising daily cycles in mammalian physiology and behaviour. The roles of the various SCN cell types in communicating timing information to downstream physiological systems remain incompletely understood, however. In particular, while vasoactive intestinal polypeptide (VIP) signalling is essential for SCN function and whole animal circadian rhythmicity, the specific contributions of VIP cell output to physiological control remains uncertain. Here we reveal a key role for SCN VIP cells in central clock output. Using multielectrode recording and optogenetic manipulations, we show that VIP neurons provide coordinated daily waves of GABAergic input to target cells across the paraventricular hypothalamus and ventral thalamus, supressing their activity during the mid to late day. Using chemogenetic manipulation, we further demonstrate specific roles for this circuitry in the daily control of heart rate and corticosterone secretion, collectively establishing SCN VIP cells as influential regulators of physiological timing

On the Performance of MRC Receiver with Unknown Timing Mismatch-A Large Scale Analysis

There has been extensive research on large scale multi-user multiple-input multiple-output (MU-MIMO) systems recently. Researchers have shown that there are great opportunities in this area, however, there are many obstacles in the way to achieve full potential of using large number of receive antennas. One of the main issues, which will be investigated thoroughly in this paper, is timing asynchrony among signals of different users. Most of the works in the literature, assume that received signals are perfectly aligned which is not practical. We show that, neglecting the asynchrony can significantly degrade the performance of existing designs, particularly maximum ratio combining (MRC). We quantify the uplink achievable rates obtained by MRC receiver with perfect channel state information (CSI) and imperfect CSI while the system is impaired by unknown time delays among received signals. We then use these results to design new algorithms in order to alleviate the effects of timing mismatch. We also analyze the performance of introduced receiver design, which is called MRC-ZF, with perfect and imperfect CSI. For performing MRC-ZF, the only required information is the distribution of timing mismatch which circumvents the necessity of time delay acquisition or synchronization. To verify our analytical results, we present extensive simulation results which thoroughly investigate the performance of the traditional MRC receiver and the introduced MRC-ZF receiver

Impact of switching from fall to spring fertilizer application : "an economic analysis of N2O reducing seeding systems in Saskatchewan"

Nitrogen (N) fertilizer applied in the fall has been shown to increase emissions of N2O a GHG (Nyborg et al. 1997). Applying N fertilizer in the spring is a management technique Saskatchewan grain and oilseed producers can use to reduce N2O emissions. The hypothesis of this thesis is that fall application of N fertilizer is more profitable than spring application. Factors to consider in the timing of fertilizer application include, the level of information available, input cost, input efficiency, and application cost. The key objective of this thesis is to determine the financial impact of switching to spring N application from fall N application. Stochastic variables include fall subsoil moisture, winter precipitation, growing season precipitation, input costs, and output prices. Expected utility theory for two representative farms at two locations is used to determine optimal N fertilizer rates and the value of spring subsoil moisture information and the value of spring output price forecasts. The fixed and variable operating costs are calculated for three seeding systems. The results show that it is optimum for producers to purchase N fertilizer in the fall and apply N fertilizer in the spring. Spring subsoil moisture information, and spring output price forecasts have little value to producers committed to continuous cropping. One pass (seed and fertilize in the spring) seeding systems have lower variable and fixed costs than two pass seeding systems for producers applying large amounts of fertilizer

A Scalable Model of Cerebellar Adaptive Timing and Sequencing: The Recurrent Slide and Latch (RSL) Model

From the dawn of modern neural network theory, the mammalian cerebellum has been a favored object of mathematical modeling studies. Early studies focused on the fan-out, convergence, thresholding, and learned weighting of perceptual-motor signals within the cerebellar cortex. This led in the proposals of Albus (1971; 1975) and Marr (1969) to the still viable idea that the granule cell stage in the cerebellar cortex performs a sparse expansive recoding of the time-varying input vector. This recoding reveals and emphasizes combinations (of input state variables) in a distributed representation that serves as a basis for the learned, state-dependent control actions engendered by cerebellar outputs to movement related centers. Although well-grounded as such, this perspective seriously underestimates the intelligence of the cerebellar cortex. Context and state information arises asynchronously due to the heterogeneity of sources that contribute signals to compose the cerebellar input vector. These sources include radically different sensory systems - vision, kinesthesia, touch, balance and audition - as well as many stages of the motor output channel. To make optimal use of available signals, the cerebellum must be able to sift the evolving state representation for the most reliable predictors of the need for control actions, and to use those predictors even if they appear only transiently and well in advance of the optimal time for initiating the control action. Such a cerebellar adaptive timing competence has recently been experimentally verified (Perrett, Ruiz, & Mauk, 1993). This paper proposes a modification to prior, population, models for cerebellar adaptive timing and sequencing. Since it replaces a population with a single clement, the proposed Recurrent Slide and Latch (RSL) model is in one sense maximally efficient, and therefore optimal from the perspective of scalability.Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-92-J-1309, N00014-93-1-1364, N00014-95-1-0409)

Modeling and analysis of semiconductor manufacturing processes using petri nets

This thesis addresses the issues in modeling and analysis of multichip module (MCM) manufacturing processes using Petri nets. Building such graphical and mathematical models is a crucial step to understand MCM technologies and to enhance their application scope. In this thesis, the application of Petri nets is presented with top-down and bottom-up approaches. The theory of Petri nets is summarized with its basic notations and properties at first. After that, the capability of calculating and analyzing Petri nets with deterministic timing information is extended to meet the requirements of the MCM models. Then, using top-down refining and system decomposition, MCM models are built from an abstract point to concrete systems with timing information. In this process, reduction theory based on a multiple-input-single-output modules for deterministic Petri nets is applied to analyze the cycle time of Petri net models. Besides, this thesis is of significance in its use of the reduction theory which is derived for timed marked graphs - an important class of Petri nets

Maximizing the Use of Computational Resources in Multi-Camera Feedback Control

In vision-based feedback control systems, the time to obtain sensor information is usually non-negligible, and these systems thereby possess fundamentally different timing behavior compared to standard real-time control applications. For many image-based tracking algorithms, however, it is possible to trade-off the computational time versus the accuracy of the produced position/orientation estimates.This paper presents a method for optimizing the use of computational resources in a multi-camera based positioning system. A simplified equation for the covariance of the position estimation error is calculated, which depends on the set of cameras used and the number of edge detection points in each image. An efficient algorithm for selection of a suitable subset of the available cameras is presented, which attempts to minimize the estimation covariance given a desired, pre-specified maximum input-output latency of the feedback control loop.Simulations have been performed that capture the real-time properties of the vision-based tracking algorithm and the effects of the timing on the performance of the control system. The suggested strategy has been compared with heuristic algorithms, and it obtains large improvements in estimation accuracy and performance for objects both in free motion and under closed-loop position control

Spike processing model of the brain

The timing of a spike within a specific time period is used to identify a place in space (input terminal) and/or sense changes in energy or position in the environment, and is used to determine the motion of an actuator or the activation of a place in space (output terminal). The timing of a spike is specified by a sensor or a time delay memory cell that is preset (predetermined) or set through experience (empirical). Time delay memory cells are arranged in decoding networks that activate specific output terminals based upon the timing of incoming spike trains, or arranged in encoding networks that generate spike trains from activated input terminals. These spike trains form semi-axes that can transmit large quantities of information in one direction through a single conductor, and are essential in the transmission of information from peripheral neurons to and from the brain through the spinal chord