Human Identification Based on Color Stimuli

Wavelet-Based Identification of Linear Discrete-Time Systems

This paper introduces four block joint detection (JD) receivers which combining the orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA) techniques, i.e., OFDM-CDMA receiver. The performance of the OFDM-CDMA receiver with orthogonal and non-orthogonal spreading sequences is investigated in mobile radio channels. The sequences considered as spreading codes are orthogonal Walsh-Hadamard, Orthogonal Gold, Gold and maximim length sequences or m - sequences. The JD algorithms for the OFDM- CDMA receiver are Zero Forcing Block Linear Equalizer (ZF- BLE), Minimum Mean Square Error Block Linear Equalizer (MMSE-BLE), with and without decision feedback (DF). Time- domain equalization does not require DFT or FFT operations and can be used to compensate the channel fading effect. Hence for hardware implementation, the time domain interpretation can lead to a more efficient structure when compared with the frequency domain approach. The bit error rate (BER) performance comparisons of different spreading codes and equalizers are shown in the simulations.

This paper investigates the placement of training symbols within the data packets of a wireless system in which transmissions are subject to asynchronous interference. The minimum mean square error of the training-based channel estimator is expressed as a function of the Fisher information of the received signal. It is shown that the placement that minimizes the minimum mean square error should be searched for within a set containing half as many elements as the number of training symbols in the packet. Furthermore, a lower bound on the minimum mean square error is derived and analyzed. It is shown that this bound is tight when the power of the interference is high. The placement of the training symbols in two clusters of equal or quasiequal length at the two edges of the data packet minimizes the lower bound for all values of the parameters and, thus, gives the solution of the problem for high values of the interference power. The influence of the training symbols placement on the data transmission performance is also investigated.

The dependence of lightness, hue and saturation changes of primary and secondary colours on the thickness of cyan, magneta, yellow and black process ink layers, as well as the space of colours that could be reproduced from those on a paper base, were determined. It was demonstrated, among others, that the volume of the solid body of reproducible colours, represented by a dodecahedron with vertices determined by the coordinates of the primary, secondary, black and white colours in the CIELAB space, increased with the increase of thickness of overprint ink film only to a certain maximum, after which a slow but steady decrease was observed. It was found that the maximum number of reproducible colours on a press print was obtained with the ink layer thickness of about 1.2µm.

We generalize the multiuser (CDMA spread spectrum) communication systems to the fading environments. We first extend Verdu's (1986) conventional optimum receiver to Rayleigh-fading environments and then evaluate its performance. Having no knowledge of the received power at the receiving end, we therefore need an estimator to efficiently estimate the received signal strength of each user in fading environments. A linear minimum mean square error (LMMSE) unbiased estimator is proposed to attain this goal. By using the minimum mean square error (MMSE) Bayesian estimation, we further propose the LMMSE bit estimator for efficient demodulation. Its performance is close to the optimum multiuser receiver but with a much simpler polynomial complexity. To further reduce the complexity, we extend the LMMSE estimator to the sequential LMMSE estimator. In sequential estimation, we do not need to implement the matched filter banks and to perform the matrix inversion when estimating. In addition, it converges after approximately 2k iterations, where k is the number of users. With this fast convergence property and the simple structure, the sequential LMMSE estimator provides an attractive alternative to the implementation of a multiuser system.

In present days, there has been a race among the communication systems in different schemes and generations. Gradually the transmission rate of data is increasing tremendously and breaking the previous generation's record. Now people are thinking of transmitting data beyond imagination. Using multiple antennas both at transmitter and receiver side, MIMO wireless technology efficiently provides very high spectral efficiency, boost the data transmission rate, enhance link reliability and improve system coverage. While transmitting data over mobile radio channels at high bit rates, the impulse response of the channel can be extended over a lot of symbol periods, leading fading and Inter-symbol interference (lSI). Equalizers are used to minimize Fading and interference effects. The analysis of the paper is studying the performance of Minimum mean square error method in terms of BER for MIMO (2×2) and (3×3) wireless channels. Binary Phase Shift Keying (BPSK) modulation technique was used in Rayleigh flat fading channel. Simulating in MATLAB results show that Minimum mean square error (MMSE) receivers is good for noise free channel and is successful in removing ISI. Successive interference method with optimal ordering outperforms the MMSE however a few problems arise because of iterative nature of the algorithm.

Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation used in a variety of broadband systems, such as asymmetric digital subscriber lines, very-high-speed digital subscriber lines, digital video and audio broadcasting, and wide local area network standards. OFDM is a promising solution achieving high data rates in a mobile environment. In wireless communication systems, signal distortion and attenuation in transmission caused by multipath effects makes it necessary to obtain knowledge related to the channel impulse response using channel estimation to provide compensation. This study combined a back propagation neural network for the estimation of channel and compensation signals with a genetic algorithm to improve performance and the convergence rate. We compared bit error rates and the mean square error of the proposed neural network with that of the conventional neural network, the least square (LS) algorithm, and the minimum mean square error (MMSE) algorithm in existing OFDM channel environments. Our results demonstrate that the proposed algorithm outperforms the LS algorithm and is on par with the MMSE algorithm.

An adaptive scaled mean square error (SMSE) filter using a Hopfield neural-network-based algorithm is presented. We show the development of the original SMSE filter from the minimum mean square error (MMSE) filter and the parametric mean square error (PMSE) filter, both of which suffer from the oversmooth phenomena. The SMSE filter is more efficient than the PMSE filter in terms of noise removal as it does not take into account all the correlation factors used for image enhancement. To further improve the performance of the SMSE filter, an adaptive approach is introduced. The adaptive SMSE filter uses a mask operation technique. A userdefined mask is moved across the image and the filtering parameters are computed based on the local image statistics of the region below the mask. The original and the adaptive SMSE filters are implemented using a Hopfield neural-network-based algorithm. A number of experiments were performed to test the filter characteristics.

In time division-synchronous code division multiple access systems, the channel estimation for multiple subscribers requires the computation of very complicated algorithms through short training sequences. This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. Simulation results of the normalized mean square error for the above mentioned estimators showed the superiority of reduced rank estimators. Multi-user joint data detectors based linear equalizers are used to suppress inter-symbol interference and mitigate intra-cell multiple access interference. The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. The results of bit error rate simulation have shown that reduced rank-JCE based detectors have an improvement by 5 dB lower than other traditional full rank-JCE based detectors.

An introductory level laboratory experiment is presented in which students learn about color using spectroscopy and chromatography. The pedagogical approach is discovery-based; students are given only enough background information to enable them to take good data. Commercially available dyes are dissolved in water to make concentrated stock solutions, which students then dilute to prepare solutions of primary, secondary and tertiary colors. The class works as a team to study colored solutions representing a range of concentrations and combinations of the three primary colors: cyan, yellow, and magenta. Students record transmission and absorption spectra and compare the results with human perception. They show the number of components in each solution by paper chromatography. They explore the filter nature of dyes, the effects of concentration, and the cumulative effects of mixing dyes. From this information they deduce the principles of color printing. The experiment is best performed with a photodiode array spectrophotometer; alternative approaches include spectrometers and simple spectroscopes which the students make from cereal boxes. The experiment can be performed in either a single three-hour laboratory period, or alternatively, three one-hour sessions.

The role of perception, language, and preference in the developmental acquisition of basic color terms

Lung cancer classification using neural networks for CT images

With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowded and messy situation, massive MIMO is designed to work with hundreds of low-cost serving antennas at a time as well as improve the spectral efficiency at the same time. Time Division Duplexing (TDD) has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. Least Square (LS), Minimum Mean Square Error (MMSE) and Linear Minimum Mean Square Error (LMMSE) are the estimators commonly used for estimating channel matrices. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of Genetic Algorithm (GA) worked well on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms. GA provides optimal result in some few iterations in terms of Mean Square Error (MSE) with respect to SNRand computational complexity.

In single-carrier aeronautical communication systems, the time-varying multipath propagation characteristics of the channel give rise to severe inter-code interference. Radio channel distortion compensation and inter-code interference cancellation are generally achieved by equalization techniques. In this paper, zero-forcing equalization, minimum mean square error equalization and minimum mean square error adaptive equalization algorithms for SC-FDE systems are investigated, but the traditional LMS algorithms cannot meet the performance requirements of convergence speed and steady-state error at the same time because the step size factor is fixed. This paper investigates the variable step size LMS algorithm and proposes an improved variable step size LMS algorithm, which uses the non-linear relationship between the error factor and the error function to construct a correlation correction function, to regulate the error factor in a small range, and to further correct the step size factor through the change of the error factor. The LMS algorithm is divided into a training mode and a tracking mode, and the two modes are combined to achieve a faster convergence rate. The computer simulation results are consistent with the theoretical analysis and confirm that the algorithm outperforms the original algorithm.

In TDD-CDMA, the detection method conventionally is MMSE-BDFE (minimum mean square error-block decision feedback equalization) based joint detection. MMSE-IC is an efficient detection algorithm in V-BLAST. To adopt the advantages of MMSE-IC (minimum mean square error-interference cancellation), we can embed MMSE-BDFE into MMSE-IC. Furthermore, we can postpone the interference cancellation after decoding, and joint detect the remained users' data from the remained signals in the next iteration. By the aid of interference cancellation after decoding, the decoding decision gain and interference cancellation gain can be obtained, so the performance is improved especially when the users' number is large. The experiments show that the proposed methods have better performance.