In this paper, a spectral domain method named the SDF (Spectral Density Fitting) method for intra-die spatial correlation function extraction is presented. Based on theoretical analysis of random field, the spectral density, as the spectral domain counterpart of correlation function, is employed to estimate the parameters of the correlation function effectively in the spectral domain. Compared with the existing extraction algorithm in the original spatial domain, the SDF method can obtain the same quality of results in the spectral domain. In actual measurement process, the unavoidable measurement error with arbitrary frequency components would greatly confound the extraction results. A filtering technique is further developed to diminish the high frequency components of the measurement error and recover the data from noise contamination for parameter estimation. Experimental results have shown that the SDF method is practical and stable.

This Letter proposes an optimal gain filter for the perceptual acoustic echo suppressor. We designed an optimally-modified log-spectral amplitude estimation algorithm for the gain filter in order to achieve robust suppression of echo and noise. A new parameter including information about interferences (echo and noise) of single-talk duration is statistically analyzed, and then the speech absence probability and the a posteriori SNR are judiciously estimated to determine the optimal solution. The experiments show that the proposed gain filter attains a significantly improved reduction of echo and noise with less speech distortion.

To mitigate the asynchronous ICI (Inter-Cell Interference), SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise should be accurately estimated for MIMO-OFDMA (Multiple-input Multiple-output-Orthogonal Frequency Division Multiple Access) system. Generally, it is assumed that the SCM of the asynchronous ICI plus background noise is estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and considering that training symbols are not appropriate for OFDMA system such as LTE (3GPP Long Term Evolution). Therefore, noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce noise effectively minimizing estimation error caused by the spectral leakage but also can be implemented using frequency-domain weighted moving average filter easily. We also consider the iterative CFR (Channel Frequency Response) and SCM estimation method which can effectively reduce the estimation error of both CFR and SCM, and improve the performance for LTE system. By using computer simulation, we show that the proposed method can provide up to 2.5 dB SIR (Signal to Interference Ratio) gain compared with the conventional method, and verify that the proposed method is attractive and suitable for implementation with stable operation.

In this paper, we propose a novel search and selection method for spreading code set of UWB system and apply it to IEEE 802.15.4a IR-UWB system. To find a spreading code with low spectral peak to average ratio (SPAR) and good auto-correlation property, the proposed method searches spreading codes in the frequency domain based on the time-frequency relation of the spreading code. Using evaluation parameters, we selected the code set which had SPAR reduced about 1.1079 dB, Golay merit factor (GMF) improved by 49% and almost the same modified Golay merit factor (MGMF) compared to the code set used as preambles for IR-UWB system.

The present paper describes quality enhancement of speech corrupted by an additive background noise in a single-channel system. The proposed approach is based on the introduction of a perceptual criterion using a frequency-weighting filter in a subtractive-type enhancement process. Although this subtractive-type method is very attractive because of its simplicity, it produces an unnatural and unpleasant residual noise. Thus, it is difficult to select fixed optimized parameters for all speech and noise conditions. A new and effective algorithm is thus developed based on the masking properties of the human ear. This newly developed algorithm allows for an automatic adaptation in the time and frequency of the enhancement system and determines a suitable noise estimate according to the frequency of the noisy input speech. Experimental results demonstrate that the proposed approach can efficiently remove additive noise related to various kinds of noise corruption.

In a multi-user orthogonal frequency division multiplexing (OFDM) system, efficient resource allocation is required to provide service to more users. In this letter, we propose an improved subcarrier allocation algorithm that can increase the spectral efficiency and the number of total transmission bits even if the number of users is too large. The proposed algorithm is divided into two stages. In the first stage, a group of users who are eligible for services is determined by using the bit error rate (BER), the users' minimum data rate requirement, and channel information. In the second stage, subcarriers are first allocated to the users on the basis of channel state, and then the reallocation is performed so that resource waste is minimized. We show that the proposed algorithm outperforms the conventional one on the basis of outage probability, spectral efficiency, and the number of total transmission bits through a computer simulation.

A scheme of the superimposing additional data signal in the time domain for orthogonal frequency division multiplexing (OFDM) system is proposed. The proposed scheme has a tradeoff between the degree of freedom for data transmission and inter-carrier interference (ICI), which provides the flexibility of data rate decision when the finite number of modulation and coding levels are available for the given channel condition. A performance analysis of the bit error rate (BER) confirms this tradeoff. In simulation on the practical environment which experiences multipath fading and error of channel estimation, the results show that much improvement of spectral efficiency has been achieved while keeping as nearly good bit error rate as the conventional OFDM. Moreover, the single carrier transmission of the superimposed additional data in the time domain also gives an opportunity of boosting the signal power up to the peak to average power ratio (PAPR) margin of the OFDM system.

In this paper, we propose a method for designing a set of pulses whose spectrum is efficiently contained in amplitude and bandwidth. Because these pulses are derived from and have shapes that are either equal or similar to the Hermite pulses, we name our proposed transmit pulses as spectrally efficient Hermite pulses. Given that the proposed set of pulses does not constitute an orthonormal one, we also propose a set of receive templates which permit orthonormal detection of the incoming signals at the receiver. The importance of our proposal is in the potential implementation of M-ary pulse shape modulation systems, for ultra wideband communications, with sets of pulses that are efficiently contained within a specific bandwidth and limited to a certain amplitude.

The spectral efficiency of cooperative relaying in interference-limited environments in which a given channel is spatially reused is investigated. Cooperative relaying is a promising technique that uses neighboring stations to forward the data toward the destination in order to achieve spatial diversity gain. It has been reported that by introducing cooperative relaying into communication between an isolated source-destination pair, the error rate or spectral efficiency is generally improved. However, it is not intuitively clear whether cooperative relaying can improve the performance in interference-limited environments because the simultaneous transmission of multiple stations increases the number of interference signals. Assuming the most fundamental cooperative relaying arrangement, which consists of only one relay station, numerical results reveal that cooperative relaying is not always superior to non-cooperative single-hop and two-hop transmissions in terms of spectral efficiency.

In a D.C.42 V-10A resistive circuit, break arcs are generated between electrical contact pairs. The materials of the contact pairs are Ag, Ag/C 2wt%, Ag/SnO2 12wt%, and Ag/ZnO 12wt%. The arc spectral intensities are measured by a time-resolved spectroscopic temperature measurement system. The arc temperature is calculated from the spectral intensities by using the method of relative intensities of two spectra. The experimental results are as follows. The arc temperature gradually decreases with increase of the gap of electrical contacts. The ranges of arc temperature for Ag, Ag/C 2wt%, Ag/SnO2 12wt%, and Ag/ZnO 12wt% contacts pairs are 4500-11000 K, 4000-6000 K, 4000-7000 K, and 4000-11000 K, respectively.

This paper proposes a spectroscopic method and system for preventing spoofing of biometric authentication. One of its focus is to enhance biometrics authentication with a spectroscopic method in a multi-factor manner such that a person's unique 'spectral signatures' or 'spectral factors' are recorded and compared in addition to a non-spectroscopic biometric signature to reduce the likelihood of imposter getting authenticated. By using the 'spectral factors' extracted from reflectance spectra of real fingers and employing cluster analysis, it shows how the authentic fingerprint image presented by a real finger can be distinguished from an authentic fingerprint image embossed on an artificial finger, or molded on a fingertip cover worn by an imposter. This paper also shows how to augment two widely used biometrics systems (fingerprint and iris recognition devices) with spectral biometrics capabilities in a practical manner and without creating much overhead or inconveniencing their users.

Cognitive Radio is an advanced enabling technology for efficient utilization of vacant spectrum due to its ability to sense the spectrum environment. Various detection methods have been proposed for spectrum sensing, which is the key function in implementing cognitive radio. However most of the existing methods put their interests in detecting TV signal and wireless microphone signals. In this paper, we explore the periodicity of the equally spaced pilot subcarriers in OFDM signal. Simulations in various fading environments show that the proposed cyclostationarity based detection method works well for OFDM signal.

This paper proposes a novel technique in designing the optimum pulse shape for ultra wideband (UWB) systems under the presence of timing jitter. In the UWB systems, pulse transmission power and timing jitter tolerance are crucial keys to communications success. While there is a strong desire to maximize both of them, one must be traded off against the other. In the literature, much effort has been devoted to separately optimize each of them without considering the drawback to the other. In this paper, both factors are jointly considered. The proposed pulse attains the adequate power to survive the noise floor and at the same time provides good resistance to the timing jitter. The proposed pulse also meets the power spectral mask restriction as prescribed by the Federal Communications Commission (FCC) for indoor UWB systems. Simulation results confirm the advantages of the proposed pulse over other previously known UWB pulses. Parameters of the proposed optimization algorithm are also investigated in this paper.

Users require speech recognition systems that offer rapid response and high accuracy concurrently. Speech recognition accuracy is degraded by additive noise, imposed by ambient noise, and convolutional noise, created by space transfer characteristics, especially in distant talking situations. Against each type of noise, existing model adaptation techniques achieve robustness by using HMM-composition and CMN (cepstral mean normalization). Since they need an additive noise sample as well as a user speech sample to generate the models required, they can not achieve rapid response, though it may be possible to catch just the additive noise in a previous step. In the previous step, the technique proposed herein uses just the additive noise to generate an adapted and normalized model against both types of noise. When the user's speech sample is captured, only online-CMN need be performed to start the recognition processing, so the technique offers rapid response. In addition, to cover the unpredictable S/N values possible in real applications, the technique creates several S/N HMMs. Simulations using artificial speech data show that the proposed technique increased the character correct rate by 11.62% compared to CMN.

This paper proposes a new algorithm named Adaptive Running Spectrum Filtering (ARSF) to restore the amplitude spectra of speech corrupted by additive noises. Based on the pre-hand noise estimation, adaptive filtering is used in speech modulation spectra according to the noise conditions. The periodic structures in the amplitude spectra are kept against noise distortion. Since the amplitude spectral structures contain the information of fundamental frequency, which is the inverse of pitch period, ARSF algorithm is added into robust pitch detection to increase the accuracy. Compared with the conventional methods, experimental results show that the proposed method significantly improves the robustness of pitch detection against noise conditions with several types and SNRs.

In this paper, we propose a new code set which has very low spectral peak to average ratio (SPAR) and good correlation properties for DS-UWB. The codes which have low SPAR are suitable for DS-UWB system which operates in UWB (3.110.4 GHz) because they can utilize more power than high SPAR codes can do. And, in order to reduce inter symbol interference (ISI) and inter piconet interferences, the codes which have good auto- and cross-correlation properties must be used. In this paper, we propose three items; (1) a new code generation method which can generate good SPAR and auto-correlation codes, (2) code selection criteria, and (3) a code set, which has been selected according to the proposed selection criteria. The proposed code set has SPAR reduced about 0.22 dB and GMF improved by 30% compared to the previous code set while it is maintaining almost same cross-correlation properties. Each code of the proposed code set, therefore, has gained 1.43 dB SIR on an average compared to that of the previous code set.

A simple and efficient semi-supervised classification method is presented. An unsupervised spectral mapping method is extended to a semi-supervised situation with multiplicative modulation of similarities between data. Our proposed algorithm is derived by linearization of this nonlinear semi-supervised mapping method. Experiments using the proposed method for some public benchmark data and color image data reveal that our method outperforms a supervised algorithm using the linear discriminant analysis and a previous semi-supervised classification method.

A new type of sound source segregation method using robot-mounted microphones, which are free from strict head related transfer function (HRTF) estimation, has been proposed and successfully applied to three simultaneous speech recognition systems. The proposed segregation method is executed with sound intensity differences that are due to the particular arrangement of the four directivity microphones and the existence of a robot head acting as a sound barrier. The proposed method consists of three-layered signal processing: two-line SAFIA (binary masking based on the narrow band sound intensity comparison), two-line spectral subtraction and their integration. We performed 20 K vocabulary continuous speech recognition test in the presence of three speakers' simultaneous talk, and achieved more than 70% word error reduction compared with the case without any segregation processing.

In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pair (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods by investigating the distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. Next, the proposed techniques are applied to the predictive vector quantizer (PVQ) used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064 dB and the percentage of outliers compared with the PVQ without any compensation, resulting in transparent quality of spectral quantization. Finally, the comparison of speech quality using the perceptual evaluation of speech quality (PESQ) measure is performed and it is shown that the IS-641 speech coder employing the proposed techniques has better decoded speech quality than the standard IS-641 speech coder.

Digital hearing aid users often complain of difficulty in understanding speech in the presence of background noise. To improve speech perception in a noisy environment, various speech enhancement algorithms have been applied in digital hearing aids. In this study, a speech enhancement algorithm using modified spectral subtraction and companding is proposed for digital hearing aids. We adjusted the biases of the estimated noise spectrum, based on a subtraction factor, to decrease the residual noise. Companding was applied to the channel of the formant frequency based on the speech presence indicator to enhance the formant. Noise suppression was achieved while retaining weak speech components and avoiding the residual noise phenomena. Objective and subjective evaluation under various environmental conditions confirmed the improvement due to the proposed algorithm. We tested segmental SNR and Log Likelihood Ratio (LLR), which have higher correlation with subjective measures. Segmental SNR has the highest and LLR the lowest correlation of the methods tested. In addition, we confirmed by spectrogram that the proposed method significantly reduced the residual noise and enhanced the formants. A mean opinion score that represented the global perception score was tested; this produced the highest quality speech using the proposed method. The results show that the proposed speech enhancement algorithm is beneficial for hearing aid users in noisy environments.