Probability Of Recognition Research Articles

Simple Markovian Equilibria in Dynamic Spatial Legislative Bargaining

The paper proves, by construction, the existence of Markovian equilibria in a model of dynamic spatial legislative bargaining. Players bargain over policies in an infinite horizon. In each period, a majority vote takes place between the proposal of a randomly selected player and the status-quo, the policy last enacted. This determines the policy outcome that carries over as the status-quo in the following period; the status-quo is endogenous. Proposer recognition probabilities are constant and discount factors are homogeneous. The construction relies on simple strategies determined by strategic bliss points computed by the algorithm we provide. A strategic bliss point is the policy maximizing the dynamic utility of a player with ample bargaining power. Relative to a bliss point, the static utility ideal, a strategic bliss point is a moderate policy. Moderation is strategic and germane to the dynamic environment; players moderate in order to constrain the future proposals of opponents. Moderation is a strategic substitute; when a player's opponents do moderate, she does not, and when they do not moderate, she does. We prove that the simple strategies induced by the strategic bliss points computed by the algorithm deliver a Stationary Markov Perfect equilibrium. Thus we prove its existence in a large class of symmetric games with more than three players and (possibly with slight adjustment) in any three-player game. Because the algorithm constructs all equilibria in simple strategies, we provide their general characterization, and we show their generic uniqueness. Finally, we analyse how the degree of moderation changes with changes in the model parameters, and we discuss the dynamics of the equilibrium policies.

Vocal-tract length estimation

Two methods for estimating the vocal-tract length equivalent to the homogeneous acoustic tube length are investigated. One method is based on calculating the tract length from the difference between the frequencies of the adjacent local spectral maxima, which exceed 4 kHz. In the other method, the vocal-tract length is calculated according to the average frequency of the second formant determined by the frequencies of first three formants. In addition, various variants of analysis are discussed irrespective of the context and with allowance for known vowels. The probability that the speaker gender is correctly recognized via two methods is about 13%, and its value is almost independent of the knowledge of the context. The probabilities that male and female voices are correctly recognized according to the difference of higher formants are, respectively, 31 and 25.5% regardless of the context and 37 and 31% with allowance for it. The probabilities of correct recognition of male and female voices reach to 27 and 21.5%, respectively, if context-independent recognition is performed from the average frequency of the second formant and 43 and 35.5% after context-dependent recognition with the known vowel type.

퍼지 알고리즘을 이용한 전자정보의 펄스 내 변조 인식

수집된 전자 정보 신호를 분석하여 활동 중인 레이더를 식별하는 ELINT 시스템은 현대 전자전에서 매우 중요한 역할을 담당한다. 수집된 신호로부터 추출할 수 있는 여러 레이더 운용 변수 중 펄스 내 변조 방식은 점점 고도화되는 레이더의 식별에 필수적인 정보이다. 본 논문은 퍼지 알고리즘을 이용하여 수집 신호에 적용된 펄스 내 변조 방식을 인식하는 기법을 제안한다. 제안하는 기법은 신호를 특징짓기 위한 퍼지 멤버십 함수와 이를 이용하여 적용된 변조방식을 추론하기 위한 퍼지 추론 규칙을 정의한다. 실험 결과는 제안된 기법이 SNR 10dB 이상의 수집 환경 하에서 95% 이상의 변조 방식 인식률을 보장함을 보인다. The ELINT system which derives intelligence from electromagnetic radiations plays an important role in modern electric warfares. Among radar characteristics inferred from the signals, intra-pulse modulation scheme is a useful feature to identify modern radars. This paper proposes the method to classify intra-pulse modulation schemes such as UM, PSK, BFSK, QFSK, LFM and NLFM based on the fuzzy algorithm. The proposed method defines fuzzy membership functions to characterize input signals, and then it calculates accordance rates for each modulation scheme with fuzzy inference rules. The experimental results show that the probability of correct recognition is more than 95% for SNR > 10dB.

High-Quality 3-D InISAR Imaging of Maneuvering Target Based on a Combined Processing Approach

In order to enhance the target recognition probability in the inverse synthetic aperture radar (ISAR) imaging domain, the interferometric ISAR (InISAR) mode is presented to achieve the 3-D information of a target. However, the real data results of a maneuvering target are not enough, due to the difficult signal processing. In this letter, a combined processing approach is proposed to realize high-quality 3-D imagery of a maneuvering target. In the approach, the range alignment and phase adjustment are implemented together on echoes to avoid destroying the coherence of the echoes. Then, the high-quality 3-D InISAR imagery of the maneuvering target can be reached. Real data results are provided to confirm the effectiveness of the proposal.

Waveform design for wideband radar target recognition based on eigensubspace projection

Transmission waveform design based on the target and the surrounding environment plays an important role in wideband target recognition radar, which could be helpful to enlarge the separation between the received echoes of different targets. However, precise prior knowledge of target–radar orientation is usually difficult to obtain, whereas target impulse response is sensitive to target–radar orientation. Therefore that has become a barrier for the waveform design. In this study, the authors propose an eigensubspace projection-based method to enlarge the separation between the received echoes of different targets with additive coloured Gaussian noise, after analysing the upper bound on the error probability of multi-target recognition. Numerical results show that the proposed method is able to improve the recognition rates effectively.

A blind modulation identification algorithm for STBC systems using multidimensional ICA

SUMMARYBlind parameter identification is a research topic of high importance for both military and civilian communication systems. To our knowledge, there is no report in literature on blindly recognizing the modulation of noncooperative MIMO systems in association with space–time block code where channel state information and coding matrix are unavailable. In this paper, we first present a classifier based on maximum likelihood on the condition of virtual channel matrix; second, the modulations are classified into two classes according to the independence of the source signals: independent and groupwise independent constellations. In the next step, a multidimensional independent component analysis algorithm is proposed by utilizing the block‐diagonal structure of the cumulant matrices to estimate the virtual channel matrix for these two cases, respectively. Last, the ambiguities are removed partly, and the classifier is proven to be insensitive to the remaining indeterminacy. Parallel computation technique is adopted to accelerate the computation of the logarithm likelihood function. Simulations show that our algorithm can work with high recognition probabilities in noncooperative space–time block code communication systems. Copyright © 2013 John Wiley & Sons, Ltd.

Automatic corn plant location and spacing measurement using laser line-scan technique

Identifying corn plant location and/or spacing is important for predicting yield potential and making decisions for in-season nitrogen application rate. In this study, an automatic corn stalk identification system based on a laser line-scan technique was developed to measure stalk locations during corn mid-growth stages. A laser line-scan technique is advantageous in this application because the line-scan data sets taken from various points of view of a plant stalk results in less interference and higher probability of plant recognition. Data were collected for two 10-meter-long corn rows at the growth stages of V8 and V10 using a mobile test platform in 2011. Each potential stalk cluster was identified in a scan and registered with the same stalks in previous scans. The final location of a stalk was the average of the measured locations in all scans. The current system setup with data processing algorithms achieved 24.0 and 10.0 % of mean total errors in plant counting at the V8 and V10 growth stages, respectively. The root-mean-squared error (RMSE) between system measured plant locations and manually measured ones were 2.3 and 2.6 cm at the V8 and V10 growth stages, respectively. The interplant spacing measured by the developed system had a good correlation with the manual measurement with an R 2 of 0.962 and 0.951 for the V8 and V10 growth stages, respectively. This system can be ultimately integrated in a variable-rate-spraying system to improve real-time, high spatial resolution variable-rate nitrogen applications.

Indirect target detection method in FLIR image sequences

Due to the complexity of the scene, target detection in forward-looking infrared (FLIR) imagery is a challenging problem, especially for occluded target. The main contribution of this paper is to propose an indirect detection method for improving the recognition probability and effectiveness of target detection method in FLIR image sequences under complex conditions. The proposed method mainly includes four steps: preparation of forward-looking reference image of landmark, extraction of the real-time scene image, template matching and target location, in which some key technologies are proposed, such as perspective transformation used to solve projective problems, position prediction for improving real-time performance, and target location used for identifying the target’s position. Experimental results are shown to demonstrate the robustness and efficiency of proposed method in FLIR image sequences.

The Condorcet Paradox Revisited

We analyze the simplest Condorcet cycle with three players and three alternatives within a strategic bargaining model with recognition probabilities and costless delay. Mixed consistent subgame perfect equilibria exist whenever the geometric mean of the agents' risk coefficients, ratios of utility differences between alternatives, is at most one. Equilibria are generically unique, Pareto efficient, and ensure agreement within finite expected time. Agents propose best or second-best alternatives. Agents accept best alternatives, may reject second-best alternatives with positive probability, and reject otherwise. For symmetric recognition probabilities and risk coefficients below one, agreement is immediate and each agent proposes his best alternative.

Maximizing Phoneme Recognition Accuracy for Enhanced Speech Intelligibility in Noise

An effective measure of speech intelligibility is the probability of correct recognition of the transmitted message. We propose a speech pre-enhancement method based on matching the recognized text to the text of the original message. The selected criterion is accurately approximated by the probability of the correct transcription given an estimate of the noisy speech features. In the presence of environment noise, and with a decrease in the signal-to-noise ratio, speech intelligibility declines. We implement a speech pre-enhancement system that optimizes the proposed criterion for the parameters of two distinct speech modification strategies under an energy-preservation constraint. The proposed method requires prior knowledge in the form of a transcription of the transmitted message and acoustic speech models from an automatic speech recognition system. Performance results from an open-set subjective intelligibility test indicate a significant improvement over natural speech and a reference system that optimizes a perceptual-distortion-based objective intelligibility measure. The computational complexity of the approach permits use in on-line applications.

A New Method for BCH Codes of Blind Recognition

According to the invariance property of the BCH code and Euclidean algorithm to calculate the greatest common factor (GCF) between code group and its cyclic shift code group. There is a method by using the degree distribution probability sum function of the greatest common factor to recognize the code length of BCH code. On this basis, the GCF can be extracted of the greatest degree distribution probability from the sum function, with the generator polynomial obtained by decomposing the GCF. The simulation results show that this method can achieve the recognition probability above 95% with BER of 4×10-3，and the high BER is much better to recognize the short codes.

Improvement of the efficiency of data protection by biometric identification

The article briefly considered a relatively new way to protect computer information - the use of biometric user identification. Such method can use a large number of features: features of the work at keyboard, features of the work with the mouse, and others. When implementing a biometric identification method is of interest to compare the value of individual features for recognition. It is proposed to introduce the so-called recognition parameters q, which quantifies the the value of features for individual recognition, as well as to determine the probability of correct recognition on the basis of particular feature or group of features.

Systematic Error Analysis for the Enhancement of Biometric Systems Using Soft Biometrics

This letter presents a novel probabilistic framework for augmenting the recognition performance of biometric systems with information from continuous soft biometric (SB) traits. In particular, by modelling the systematic error induced by the estimation of the SB traits, a modified efficient recognition probability can be extracted including information related both to the hard and SB traits. The proposed approach is applied without loss of generality in the case of gait recognition, where two state-of-the-art gait recognition systems are considered as hard biometrics and the height and stride length of the individuals are considered as SBs. Experimental validation on two known, large datasets illustrates significant advances in the recognition performance with respect to both identification and authentication rates.

A algorithm of fast digital phase modulation signal recognition

Classifications of digital modulation, the signal characteristics of the phase of the cycle will cause the phase wrapped and reduce overlapping signals in the received RF digital modulation automatically correct classification probability. According to the principle of minimum mean square, a phase modulation and phase modulation signal classification features as well as 2PSK and MPSK classification. The experiments illustrate the robust of the feature-based approach for automatic digital modulation classification and a higher recognition probability suitable to various pulse shaping filters, roll-off factors and symbol rates. DOI: http://dx.doi.org/10.11591/telkomnika.v10i8.1666

A hybrid multiuser detector for DS-UWB systems with matched filter and error-bit recognizer

In this article, we propose a hybrid algorithm of multiuser detection (MUD) for direct sequence ultra-wideband (UWB) communication systems, based on matched filters (MF) and error-bit recognizers (ER). The ER embraces three steps: bit mapping, K-means clustering, and sign judgment. In this detector, we construct a mapping function and map the output base-band bits from MFs into a one-dimensional feature space to get the amplitude information. After that, we set an initial value and classify the bits into right bits and wrong ones by K-means clustering. Finally, we make the sign judgment to prevent some right bits being picked out as wrong bits and correct the wrong bits to reduce the bit error rate (BER) of the system. Compared to a conventional detector based on MFs and minimum mean square error detector, to a large extent, our detector can improve the BER performance of a system because of high recognition probability of the wrong bits in K-means clustering. What is more, the simulation results show that the proposed hybrid MUD is not sensitive to the number of users. It can achieve a good BER performance and low computational complexity when there are 20 UWB transmitters in the channel.

Optimal value commitment in bilateral bargaining

We study the role of commitment as a source of strategic power in a non-cooperative bargaining game. Two impatient players bargain about the division of a shrinking surplus under a standard bargaining protocol in discrete time with constant recognition probabilities. Before bargaining, a player can commit to some part of the surplus. This commitment remains binding until the surplus has shrunk below the amount that the player is committed to. Intuitively, one cannot remain committed to something which has become impossible. The model offers insight on the relative importance of proposal power and commitment for the bargaining outcome. In a version of the game where both players may simultaneously choose their commitments, the equal split emerges from within a range of equilibrium divisions as a focal point which is robust to changes in the model parameters.

Real-Time Opto-Electronic Hybrid Joint-Transform-Correlator for Scene Matching Guidance

In this paper, an optoelectronic hybrid processing system for cruise missile scene matching guidance based on convolute structure Joint-Transform-Correlator(JTC) was proposed. By edge detection of input image and binaryzation processing of joint power spectrum, the system can achieve sharper correlation peak and location accuracy. Simulation calculation and optical experiments show that even in noisy background, the system can obtain excellent recognition and location performances with 16frames/s, recognition probability greater than 94%, and location accuracy better than a pixel. It is very advantageous to meet the demands of further improving performance, speed, and shoot accuracy of the cruise missiles.

Television produces more false recognition for news than newspapers.

In this experiment, we examined whether media format and the presence of relevant photographs influence the probability of false recognition for media content. We told participants that we were interested in what makes news interesting and asked them to watch 3 televised broadcasts or read 3 news articles that appeared with or without a photo depicting a relevant aspect of the story. Forty-eight hours later, participants completed a memory test. Overall, we found that people are good at knowing what they have and have not been exposed to; however, people who watched televised media were more likely to falsely recognize material that was not presented. The presence of photographs did not affect recognition accuracy. Our results suggest that the format in which people choose to receive their news may significantly impact recognition accuracy for news.

Upper-bound estimates for classifiers based on a dissimilarity function

Approaches to calculating upper-bound estimates of recognition probability are proposed that can be used for a more general class of models. One of estimates determines the stability of object coverage by classification algorithms on the basis of distribution of distances between objects, and another estimate is underlain by leave-one-out cross-validation. This considerably simplifies and facilitates the construction of estimates.

Simultaneous multiple target recognition using polarization agile waves

A novel matching method for simultaneous multi-target recognition is proposed by jointly considering target’s prior scattering knowledge and the polarization parameters of radar echoes. The matching coefficients are calculated for the judgment. MATLAB simulations show that several targets can be accurately recognized simultaneously, and a high recognition probability can be achieved in Monte Carlo simulations. The total execution time can be remarkably reduced in the Field Programmable Gate Array (FPGA) implementation of the matching procedure.