Modelling the information seeking user by the decision they make

The article focuses on how the information seeker makes decisions about relevance. It will employ a novel decision theory based on quantum probabilities. This direction derives from mounting research within the field of cognitive science showing that decision theory based on quantum probabilities is superior to modelling human judgements than standard probability models [2, 1]. By quantum probabilities, we mean decision event space is modelled as vector space rather than the usual Boolean algebra of sets. In this way,incompatible perspectives around a decision can be modelled leading to an interference term which modifies the law of total probability. The interference term is crucial in modifying the probability judgements made by current probabilistic systems so they align better with human judgement. The goal of this article is thus to model the information seeker user as a decision maker. For this purpose, signal detection models will be sketched which are in principle applicable in a wide variety of information seeking scenarios.

Joint Self-Iterating Equalization and Detection for Two-Dimensional Intersymbol-Interference Channels

We develop several novel signal detection algorithms for two-dimensional intersymbol-interference channels. The contribution of the paper is two-fold: (1) We extend the one-dimensional maximum a-posteriori (MAP) detection algorithm to operate over multiple rows and columns in an iterative manner. We study the performance vs. complexity trade-offs for various algorithmic options ranging from single row/column non-iterative detection to a multi-row/column iterative scheme and analyze the performance of the algorithm. (2) We develop a self-iterating 2-D linear minimum mean-squared based equalizer by extending the 1-D linear equalizer framework, and present an analysis of the algorithm. The iterative multi-row/column detector and the self-iterating equalizer are further connected together within a turbo framework. We analyze the combined 2-D iterative equalization and detection engine through analysis and simulations. The performance of the overall equalizer and detector is near MAP estimate with tractable complexity, and beats the Marrow Wolf detector by about at least 0.8 dB over certain 2-D ISI channels. The coded performance indicates about 8 dB of significant SNR gain over the uncoded 2-D equalizer-detector system.

Large-Scale Multiuser SM-MIMO Versus Massive MIMO

Spatial modulation (SM) is attractive for multiantenna wireless communications. SM uses multiple transmit antenna elements but only one transmit radio frequency (RF) chain. In SM, in addition to the information bits conveyed through conventional modulation symbols (e.g., QAM), the index of the active transmit antenna also conveys information bits. In this paper, we establish that SM has significant signal-to-noise (SNR) advantage over conventional modulation in large-scale multiuser (multiple-input multiple-output) MIMO systems. Our new contribution in this paper addresses the key issue of large-dimension signal processing at the base station (BS) receiver (e.g., signal detection) in large-scale multiuser SM-MIMO systems, where each user is equipped with multiple transmit antennas (e.g., 2 or 4 antennas) but only one transmit RF chain, and the BS is equipped with tens to hundreds of (e.g., 128) receive antennas. Specifically, we propose two novel algorithms for detection of large-scale SM-MIMO signals at the BS; one is based on message passing and the other is based on local search. The proposed algorithms achieve very good performance and scale well. For the same spectral efficiency, multiuser SM-MIMO outperforms conventional multiuser MIMO (recently being referred to as massive MIMO) by several dBs. The SNR advantage of SM-MIMO over massive MIMO can be attributed to: (i) because of the spatial index bits, SM-MIMO can use a lower-order QAM alphabet compared to that in massive MIMO to achieve the same spectral efficiency, and (ii) for the same spectral efficiency and QAM size, massive MIMO will need more spatial streams per user which leads to increased spatial interference.

Minimum-Error-Probability CFO Estimation for Multiuser MIMO-OFDM Systems

We consider carrier frequency offset (CFO) estimation in the context of multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems over noisy frequency-selective wireless channels with both single- and multiuser scenarios. We conceived a new approach for parameter estimation by discretizing the continuous-valued CFO parameter into a discrete set of bins and then invoked detection theory, analogous to the minimum-bit-error-ratio optimization framework for detecting the finite-alphabet received signal. Using this radical approach, we propose a novel CFO estimation method and study its performance using both analytical results and Monte Carlo simulations. We obtain expressions for the variance of the CFO estimation error and the resultant BER degradation with the single- user scenario. Our simulations demonstrate that the overall BER performance of a MIMO-OFDM system using the proposed method is substantially improved for all the modulation schemes considered, albeit this is achieved at increased complexity.

Two-Dimensional Noise-Predictive Maximum Likelihood Method for Magnetic Recording Channels

Noise-predictive maximum likelihood (NPML) is a well known signal detection technique used in partial response maximum likelihood (PRML) scheme in 1D magnetic recording channels. The noise samples colored by the partial response (PR) equalizer are predicted/ whitened during the signal detection using a Viterbi detector. In this paper, we propose an extension of the NPML technique for signal detection in 2D ISI channels. The impact of noise prediction during signal detection is studied in PRML scheme for a particular choice of 2D ISI channel and PR targets.

Investigation Into Harmful Patterns Over Multitrack Shingled Magnetic Detection Using the Voronoi Model

Two-dimensional magnetic recording 2-D (TDMR) is a promising technology for next generation magnetic storage systems based on a systems-level framework involving sophisticated signal processing at the core. The TDMR channel suffers from severe jitter noise along with electronic noise that needs to be mitigated during signal detection and recovery. Recently, we developed noise prediction-based techniques coupled with advanced signal detectors to work with these systems. However, it is important to understand the role of harmful patterns that can be avoided during the encoding process. In this paper, we investigate the Voronoi-based media model to study the harmful patterns over multitrack shingled recording systems. Through realistic quasi-micromagnetic simulation studies, we identify 2-D data patterns that contribute to high media noise. We look into the generic Voronoi model and present our analysis on multitrack detection with constrained coded data. We show that the 2-D constraints imposed on input patterns result in an order of magnitude improvement in the bit-error rate for the TDMR systems. The use of constrained codes can reduce the complexity of 2-D intersymbol interference (ISI) signal detection, since the lesser 2-D ISI span can be accommodated at the cost of a nominal code rate loss. However, a system must be designed carefully so that the rate loss incurred by a 2-D constraint does not offset the detector performance gain due to more distinguishable readback signals.

Rapid quantitative detection of Yersinia pestis by lateral-flow immunoassay and up-converting phosphor technology-based biosensor

Up-converting phosphor technology (UPT)-based lateral-flow immunoassay has been developed for quantitative detection of Yersinia pestis rapidly and specifically. In this assay, 400 nm up-converting phosphor particles were used as the reporter. A sandwich immumoassay was employed by using a polyclonal antibody against F1 antigen of Y. pestis immobilized on the nitrocellulose membrane and the same antibody conjugated to the UPT particles. The signal detection of the strips was performed by the UPT-based biosensor that could provide a 980 nm IR laser to excite the phosphor particles, then collect the visible luminescence emitted by the UPT particles and finally convert it to the voltage as a signal. V-T and V-c stand for the multiplied voltage units for the test and the control line, respectively, and the ratio V-T/V-C is directly proportional to the number of Y pestis in a sample. We observed a good linearity between the ratio and log CFU/ml of Y pestis above the detection limit, which was approximately 10(4) CFU/mI. The precision of the intra- and inter-assay was below 15% (coefficient of variation, CV). Cross-reactivity with related Gram-negative enteric bacteria was not found. The UPT-LF immunoassay system presented here takes less than 30 min to perform from the sample treatment to the data analysis. The current paper includes only preliminary data concerning the biomedical aspects of the assay, but is more concentrated on the technical details of establishing a rapid manual assay using a state-of-the-art label chemistry. (c) 2006 Elsevier B.V. All rights reserved.

小波消噪在振动信号处理中的应用

信噪分离是小波分析中的一个有效的信号检测方法。本文在阐述了小波分析及消噪的小波理论的基础上 ,给出了从噪声污染信号中恢复原信号的实例 ,并与傅立叶分析消噪进行了比较 ,结果表明对于非平稳振动信号小波消噪的效果明显优于傅立叶变换。

陆相砂泥岩层序的高精度检测方法研究及应用

Ordos Basin is a typical cratonic petroliferous basin with 40 oil-gas bearing bed sets. It is featured as stable multicycle sedimentation, gentle formation, and less structures. The reservoir beds in Upper Paleozoic and Mesozoicare are mainly low density, low permeability, strong lateral change, and strong vertical heterogeneous. The well-known Loess Plateau in the southern area and Maowusu Desert, Kubuqi Desert and Ordos Grasslands in the northern area cover the basin, so seismic data acquisition in this area is very difficult and the data often takes on inadequate precision, strong interference, low signal-noise ratio, and low resolution. Because of the complicated condition of the surface and the underground, it is very difficult to distinguish the thin beds and study the land facies high-resolution lithologic sequence stratigraphy according to routine seismic profile. Therefore, a method, which have clearly physical significance, based on advanced mathematical physics theory and algorithmic and can improve the precision of the detection on the thin sand-peat interbed configurations of land facies, is in demand to put forward.Generalized S Transform (GST) processing method provides a new method of phase space analysis for seismic data. Compared with wavelet transform, both of them have very good localization characteristics; however, directly related to the Fourier spectra, GST has clearer physical significance, moreover, GST adopts a technology to best approach seismic wavelets and transforms the seismic data into time-scale domain, and breaks through the limit of the fixed wavelet in S transform, so GST has extensive adaptability. Based on tracing the development of the ideas and theories from wavelet transform, S transform to GST, we studied how to improve the precision of the detection on the thin stratum by GST.Noise has strong influence on sequence detecting in GST, especially in the low signal-noise ratio data. We studied the distribution rule of colored noise in GST domain, and proposed a technology to distinguish the signal and noise in GST domain. We discussed two types of noises: white noise and red noise, in which noise satisfy statistical autoregression model. For these two model, the noise-signal detection technology based on GST all get good result. It proved that the GST domain noise-signal detection technology could be used to real seismic data, and could effectively avoid noise influence on seismic sequence detecting.On the seismic profile after GST processing, high amplitude energy intensive zone, schollen, strip and lentoid dead zone and disarray zone maybe represent specifically geologic meanings according to given geologic background. Using seismic sequence detection profile and combining other seismic interpretation technologies, we can elaborate depict the shape of palaeo-geomorphology, effectively estimate sand stretch, distinguish sedimentary facies, determine target area, and directly guide oil-gas exploration.In the lateral reservoir prediction in XF oilfield of Ordos Basin, it played very important role in the estimation of sand stretch that the study of palaeo-geomorphology of Triassic System and the partition of inner sequence of the stratum group. According to the high-resolution seismic profile after GST processing, we pointed out that the C8 Member of Yanchang Formation in DZ area and C8 Member in BM area are the same deposit. It provided the foundation for getting 430 million tons predicting reserves and unite building 3 million tons off-take potential.In tackling key problem study for SLG gas-field, according to the high-resolution seismic sequence profile, we determined that the deposit direction of H8 member is approximately N-S or NNE-SS W. Using the seismic sequence profile, combining with layer-level profile, we can interpret the shape of entrenched stream. The sunken lenticle indicates the high-energy stream channel, which has stronger hydropower. By this way we drew out three high-energy stream channels' outline, and determined the target areas for exploitation. Finding high-energy braided river by high-resolution sequence processing is the key technology in SLG area.In ZZ area, we studied the distribution of the main reservoir bed-S23, which is shallow delta thin sand bed, by GST processing. From the seismic sequence profile, we discovered that the schollen thick sand beds are only local distributed, and most of them are distributary channel sand and distributary bar deposit. Then we determined that the S23 sand deposit direction is NW-SE in west, N-S in central and NE-SW in east. The high detecting seismic sequence interpretation profiles have been tested by 14 wells, 2 wells mismatch and the coincidence rate is 85.7%. Based on the profiles we suggested 3 predicted wells, one well (Yu54) completed and the other two is still drilling. The completed on Is coincident with the forecastThe paper testified that GST is a effective technology to get high- resolution seismic sequence profile, compartmentalize deposit microfacies, confirm strike direction of sandstone and make sure of the distribution range of oil-gas bearing sandstone, and is the gordian technique for the exploration of lithologic gas-oil pool in complicated areas.

Analysing energy detector diversity receivers for spectrum sensing

The analysis of energy detector systems is a well studied topic in the literature: numerous models have been derived describing the behaviour of single and multiple antenna architectures operating in a variety of radio environments. However, in many cases of interest, these models are not in a closed form and so their evaluation requires the use of numerical methods. In general, these are computationally expensive, which can cause difficulties in certain scenarios, such as in the optimisation of device parameters on low cost hardware. The problem becomes acute in situations where the signal to noise ratio is small and reliable detection is to be ensured or where the number of samples of the received signal is large. Furthermore, due to the analytic complexity of the models, further insight into the behaviour of various system parameters of interest is not readily apparent. In this thesis, an approximation based approach is taken towards the analysis of such systems. By focusing on the situations where exact analyses become complicated, and making a small number of astute simplifications to the underlying mathematical models, it is possible to derive novel, accurate and compact descriptions of system behaviour. Approximations are derived for the analysis of energy detectors with single and multiple antennae operating on additive white Gaussian noise (AWGN) and independent and identically distributed Rayleigh, Nakagami-m and Rice channels; in the multiple antenna case, approximations are derived for systems with maximal ratio combiner (MRC), equal gain combiner (EGC) and square law combiner (SLC) diversity. In each case, error bounds are derived describing the maximum error resulting from the use of the approximations. In addition, it is demonstrated that the derived approximations require fewer computations of simple functions than any of the exact models available in the literature. Consequently, the regions of applicability of the approximations directly complement the regions of applicability of the available exact models. Further novel approximations for other system parameters of interest, such as sample complexity, minimum detectable signal to noise ratio and diversity gain, are also derived. In the course of the analysis, a novel theorem describing the convergence of the chi square, noncentral chi square and gamma distributions towards the normal distribution is derived. The theorem describes a tight upper bound on the error resulting from the application of the central limit theorem to random variables of the aforementioned distributions and gives a much better description of the resulting error than existing Berry-Esseen type bounds. A second novel theorem, providing an upper bound on the maximum error resulting from the use of the central limit theorem to approximate the noncentral chi square distribution where the noncentrality parameter is a multiple of the number of degrees of freedom, is also derived.

Development of a rapid low cost fluorescent biosensor for the detection of food contaminants

A prototype fluorescent based biosensor has been developed for the antibody based detection of food related contaminants. Its performance was characterised and showed a typical antibody binding signal of 200-2000 mV, a short term noise of 9.1 mV, and baseline slope of -0.016 mV/s over 4 h. Bulk signal detection repeatability (n=23) and reproducibility (n=3) were less than 2.4%CV. The biosensor detection unit was evaluated using two food related model systems proving its ability to monitor both binding using commercial products and inhibition through the development of an assay. This assay development potential was evaluated by observing the biosensor's performance whilst appraising several labelled antibody and glass slide configurations. The molecular interaction between biotin and an anti-biotin antibody was shown to be inhibited by 41% due to the presence of biotin in a sample. A food toxin (domoic acid) calibration curve was produced, with %CVs ranging from 2.7 to 7.8%, and a midpoint of approximately 17 ng/ml with further optimisation possible. The ultimate aim of this study was to demonstrate the working principles of this innovative biosensor as a potential portable tool with the opportunity of interchangeable assays. The biosensor design is applicable for the requirements of routine food contaminant analysis, with respect to performance, functionality and cost. (C) 2012 Elsevier B.V. All rights reserved.

Compressive Sensing based Detector for Sparse Signal Modulation in Precoded OFDM

In this paper, we propose a sparse signal modulation (SSM) method for precoded orthogonal frequency division multiplexing (OFDM) systems and study the signal detection. Although a receiver is able to exploit a path diversity gain with random precoding in OFDM, the complexity of the receiver is usually high as the orthogonality is not retained due to precoding. However, with SSM, we can derive a low-complexity detector that can provide reasonably good performances with a low sparsity ratio based on the notion of compressive sensing (CS). An important feature of a CS detector is that it can estimate SSM signals with a small fraction of the received signals over sub-carriers. This feature can allow us to build a low cost receiver with a small number of demodulators.

Motion detection and motion verbs: language affects low-level visual perception

Recent theories propose that semantic representation and sensorimotor processing have a common substrate via simulation. We tested the prediction that comprehension interacts with perception, using a standard psychophysics methodology.While passively listening to verbs that referred to upward or downward motion, and to control verbs that did not refer to motion, 20 subjects performed a motion-detection task, indicating whether or not they saw motion in visual stimuli containing threshold levels of coherent vertical motion. A signal detection analysis revealed that when verbs were directionally incongruent with the motion signal, perceptual sensitivity was impaired. Word comprehension also affected decision criteria and reaction times, but in different ways. The results are discussed with reference to existing explanations of embodied processing and the potential of psychophysical methods for assessing interactions between language and perception.

Towards pain-free diagnosis of skin diseases through multiplexed microneedles: biomarker extraction and detection using a highly sensitive blotting method

Immunodiagnostic microneedles provide a novel way to extract protein biomarkers from the skin in a minimally invasive manner for analysis in vitro. The technology could overcome challenges in biomarker analysis specifically in solid tissue, which currently often involves invasive biopsies. This study describes the development of a multiplex immunodiagnostic device incorporating mechanisms to detect multiple antigens simultaneously, as well as internal assay controls for result validation. A novel detection method is also proposed. It enables signal detection specifically at microneedle tips and therefore may aid the construction of depth profiles of skin biomarkers. The detection method can be coupled with computerised densitometry for signal quantitation. The antigen specificity, sensitivity and functional stability of the device were assessed against a number of model biomarkers. Detection and analysis of endogenous antigens (interleukins 1α and 6) from the skin using the device was demonstrated. The results were verified using conventional enzyme-linked immunosorbent assays. The detection limit of the microneedle device, at ≤10 pg/mL, was at least comparable to conventional plate-based solid-phase enzyme immunoassays.

Pitch detection algorithms based on zero-cross rate and autocorrelation function for musical notes

This paper discusses two pitch detection algorithms (PDA) for simple audio signals which are based on zero-cross rate (ZCR) and autocorrelation function (ACF). As it is well known, pitch detection methods based on ZCR and ACF are widely used in signal processing. This work shows some features and problems in using these methods, as well as some improvements developed to increase their performance. © 2008 IEEE.