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Adaptive equalization plays an important role in digital communication to reduce the distortions due to inter-symbol interference. An adaptive filter is used as an equalizer model in channel equalization. An adaptive algorithm is the heart of the adaptive filter which finds the optimum coefficients of the filter. The choice of the adaptive algorithm improves the convergence rate and minimizes the mean square error (MSE). This paper aims to propose a cat swarm optimization (CSO)-based adaptive algorithm and its modification to improve the performance of a channel equalizer.

The input digital training data are transmitted through different channel conditions. A linear transversal filter is used as a channel and equalizer model. The equalizer coefficients are trained by the proposed simplified cat swarm optimization (SCSO) algorithm to find the estimated digital training data.

The performance of the proposed SCSO algorithm is compared with particle swarm optimization (PSO)-based channel equalization. The improvement in convergence rate and MSE is verified under linear and nonlinear channel conditions with different delay spreads. The optimum parameters of the SCSO are found using simulation-based sensitivity analysis.

This paper analyzes a CSO algorithm for adaptive channel equalization and proposes a SCSO algorithm to identify the optimum coefficients of a transversal equalizer. The seeking mode process is simplified in the proposed SCSO to achieve better performance in channel equalization. The proposed SCSO algorithm guarantees minimum MSE in all independent runs, whereas in PSO, few misses are possible.

A new direct blind equalization algorithm is presented in this paper. It relies on the auto‐correlation matrix of the channel, and adopts its eigenvector decomposition for designing an equalizer, which exploits the correlation characteristics of the channel. The proposed equalization is insensitive to the inaccuracy of the channel order estimation, and its data sequence length required for estimating the channel's correlation matrix is shorter than that of the other eigenvector decomposition methods that assumed that the channel order was known or had been estimated. Simulation results show that this algorithm is capable of acquiring a good performance under lower SNR in a communication system employing 16‐QAM modulation.

In this paper, the authors present different methods for reconfigurable finite impulse response (RFIR) filter design. Distributed arithmetic (DA)-based reconfigurable FIR filter design is suitable for software-defined radio (SDR) applications. The main contribution of reconfiguration is reuse of registers, multipliers, adders and to optimize various parameters such as area, power dissipation, speed, throughput, latency and hardware utilizations of flip-flops and slices. Therefore, effective design of building blocks will be optimized for RFIR filter with all the above parameters.

The modified, direct form register structure of FIR filter contributes the reuse concept and allows utilization of less number of registers and parallel computation operations. The disadvantage of DA and other conventional methods is delay increases proportionally with filter length. This is due to different partial products generated by adders. The usage of adder and multipliers in DA-FIR filter restricts the area and power dissipation because of their complexity of generation of sum and carry bits. The hardware implementation time of an adder can be reduced by parallel prefix adder (PPA) usage based on Ling equation. PPA uses shift-add multiplication, which is a repetitive process of addition, and this process is known as Bypass Zero feed multiplicand in direct multiplication, and the proposed technique optimizes area-power product efficiently. The modified DA (MDA)-based RFIR filter is designed for 64 taps filter length (N). The design is developed by using Verilog hardware description language and implemented on field-programmable gate array. Also, this design validates SDR channel equalizer.

Both RFIR and SDR are integrated as single system and implemented on Artix-7 development board of XC7A100tCSG324 and exploited the advantages in area-delay, power-speed products and energy efficiency. The theoretical and practical comparisons have been carried out, and the results are compared with existing DA-RFIR designs in terms of throughput, latency, area-delay, power-speed products and energy efficiency, which are improved by 14.5%, 23%, 6.5%, 34.2% and 21%, respectively.

The DA-based RFIR filter is validated using Chipscope Pro software tool on Artix-7 FPGA in Xilinx ISE design suite and compared constraint parameters with existing state-of-art results. It is also tested the filtering operation by applying the RFIR filter on Audio signals for removal of noisy signals and it is found that 95% of noise signals are filtered effectively.

In order to optimize BER and to substantiate performance measures, initially, the filter bank multicarrier (FBMC) quadrature amplitude modulation (QAM) performance metrics are evaluated with the cyclic prefix-orthogonal frequency division multiplexing (CP-OFDM) system. The efficiency of CP-OFDM, as well as FBMC/QAM that is transmitting over specific fading channels, is evaluated in terms of quality trade-off metrics over bit error rate (BER) as well as modulation order. When compared with the traditional FBMC systems, the proposed FBMC QAM system shows better performance. The performance metrics of FBMC/QAM with the inclusion of multiuser multiple-input-multiple-output (MUMIMO) is validated with worst case channel environment. The performance penalty gap that exists in CP- OFDM is compared with improved FBMC QAM in terms of both BER and OOB radiation measures. The BER trade off comparison between ML and MMSE optimally determine the prominent signal detection model for high performance FBMC QAM system.

The main objective of this research work is to provide perceptions about performance, co-channel interference avoidance as well as about the techniques that are used for minimizing the complexity of the system that is related to FBMC QAM structure for reducing intrinsic interference with higher spectral features as well as maximal likelihood (ML) detector systems.

This research work also looks at the efficiency of multiuser multiple-input-multiple-output (MU-MIMO) FBMC/QAM over nonlinear channels. Furthermore, when compared with OFDM, it also significantly reduces the penalty gap efficiency, thereby enabling the accessibility of the proposed FBMC QAM system from BER as well as implementation point of view. Finally, the signal detection is facilitated by the sub-detector and is achieved on the downlink side by making use of threshold-driven statistical measures that accurately minimize the complexity trade-off measures of the ML detector over modulation order. The computation of the proposed FBMC method’s BER performance measures was carried out through MATLAB simulation environments, as well as efficiency of the suggested work was demonstrated through detailed analyses.

This research work intend to combine the efficient MU-MIMO based transmission scheme with optimal FBMC/QAM for improved QoS over highly nonlinear channels which includes both delay spread and Doppler effects. And optimal signal detection model is facilitated at the downlink side by making use of threshold-driven statistical measures that accurately minimize the complexity trade-off measures of the ML detector over modulation order. The computation of the proposed FBMC method’s BER performance measures was carried out through MATLAB simulation environments, as well as efficiency of the suggested work was demonstrated through detailed analyses.

Digital signal processing (DSP) applications such as finite impulse response (FIR) filter, infinite impulse response and wavelet transformation functions are mainly constructed using multipliers and adders. The performance of any digital applications is dependent on larger size multipliers, area and power dissipation. To optimize power and area, an efficient zero product and feeder register-based multiplier (ZP and FRBM) is proposed. Another challenging task in multipliers is summation of partial products (PP), results in more delay. To address this issue, the modified parallel prefix adder (PPA) is incorporated in multiplier design. In this work, different methods are studied and analyzed for designing FIR filter, optimized with respect to area, power dissipation, speed, throughput, latency and hardware utilization.

The distributed arithmetic (DA)-based reconfigurable FIR design is found to be suitable filter for software-defined radio (SDR) applications. The performance of adder and multipliers in DA-FIR filter restricts the area and power dissipation due to their complexity in terms of generation of sum and carry bits. The hardware implementation time of an adder can be reduced by using PPA which is based on Ling equation. The MDA-RFIR filter is designed for higher filter length (N), i.e. N = 64 with 64 taps and this design is developed using Verilog hardware description language (HDL) and implemented on field-programmable gate array. The design is validated for SDR channel equalizer; both RFIR and SDR are integrated as single system and implemented on Artix-7 development board of part name XC7A100tCSG324.

The MDA-RFIR for N = 64 is optimized about 33% in terms of area-delay, power-speed product and energy efficiency. The theoretical and practical comparisons have been done, and the practically obtained results are compared with existing DA-RFIR designs in terms of throughput, latency, area-delay, power-speed product and energy efficiency are better about 3.5 times, 31, 45 and 29%, respectively.

The MDA-RFIR for N = 64 is optimized about 33% in terms of area-delay, power-speed product and energy efficiency.

A ‘noise stethoscope’ has a tropicalised moving coil, dynamic microphone and fully transistorised amplifier. It has a range from 40 to 125 decibels divided into four sub‐ranges for easier reading. It weighs 16·8oz with battery. Price is £71·50. Delivery: Ex‐stock.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

Does education still serve as a great equalizer today? Does today’s worldwide expansion of schooling foster a global economic convergence? These questions need fresh answers at this time of growing concern over inequality. Past studies have abundantly documented the effects of schooling on within-country inequality, but we know little about corresponding effects on between-country inequality. We fill this gap by drawing on two innovations. The first is to formulate a theory of global inequality that integrates international differences in both the quantity and quality of education. The second, methodological, innovation is to propose and apply a method for decomposing trends in global inequality in GDP in terms of five social forces that include the quantity and quality of schooling. Analyses focus on the 1990–2010 period. The results confirm the continued salience of education: Trends in education account for as much as 80% of the 1990–2010 decline in between-country GDP inequality. However, we find a declining significance of “quantity” over “quality.” In sum, education remains salient as a global equalizer but its salience increasingly depends on bridging international differences in school quality.

The article examines whether cross-border trade in digitally delivered services (DDSs) has an influence on European female entrepreneurship. Two research questions were asked to assess the potential impact of trade in DDSs both on the import and export sides.

To answer the research questions, the panel data for 26 European countries for the years 2008–2019 were implemented to estimate panel regression models. Based on the results of variance inflation factors (VIFs) and Breusch–Pagan and Hausman tests, the estimations of panel models were conducted for female entrepreneurship as a dependent variable and measures of import and export of digitally delivered services as independent variables.

The imports of digitally delivered services positively affect female entrepreneurship in European countries, whilst the impact of the export of digitally delivered services is statistically insignificant. The possibility of being a customer of digitally delivered services through its import may become a gender equaliser in entrepreneurship. However, as differences in digital competencies and growth intentions prevent women from acting as the providers of digitally delivered services, the export of DDSs can sustain the existing gender gap in entrepreneurship.

The research findings provide the added value in the field of female entrepreneurship, referring to institutional theory and human capital theory. The import of DDSs seems to support female entrepreneurs through the reduction of cultural distance, whilst the human capital theory gains the perspective of limited digital competencies needed to export DDSs as a pathway to the internationalisation of women's ventures. The practical implications for trade policy, digitalisation and gender equality should aim not only at supporting women's export propensity, but should also focus on the development of their digital competencies.

Instead of commonly used perspective of international entrepreneurship, the authors implemented the lens of cross-border trade to check whether there is a linkage between internationalisation, measured by imports and exports of DDSs and female entrepreneurship. Trade economists neglect the gender dimension in their studies of pro-growth internationalisation. In contrast, research on female entrepreneurship does not consider the potential of cross-border trade in DDSs as a gender equaliser.