## What is/are Single Input Single Output?

Single Input Single Output - It is a single input single output controller, which incurs low implementation complexity.^{[1]}We will derive a block diagram of a MIMO system and compact it using the concept of the equivalent baseband channel, which is described in Part I for single input single output (SISO) channels.

^{[2]}, for a channel with a single input single output (SISO).

^{[3]}To evaluate the effect of the smoothing parameter the proposed controller is first applied to a single input single output system.

^{[4]}Most of the research on active techniques have focused on single input single output (SISO) control.

^{[5]}Finally, the analytical and simulation results proved that with the help of the proposed artificial noise, both the information security and data rate performance can be significantly improved compared with that in single input single output (SISO) system.

^{[6]}The tuning methodology is applicable for single input single output and multi input multi output stable processes.

^{[7]}Single input single output (SISO) system identification is applied on IEEE 9 bus system with dynamic load changes.

^{[8]}This paper investigates the use of an adaptive slope seeking strategy for Single Input Single Output (SISO) process control.

^{[9]}In this paper we consider the blind identification problem of a single input single output (SISO) linear system.

^{[10]}Shannon in his pioneering work Shannon (Bell Syst Tech J 27:379, 1948, [1]) in the year 1948 for single input single output (SISO) channels.

^{[11]}This paper presents a PSO based design of classical Proportional-Integral (PI) controller for consistency of stock, one of the most important papermaking parameters used as a single input single output (SISO) system.

^{[12]}Researchers have extensively worked on multiband spectrum sensing in single input single output half-duplex CRNs under additive white Gaussian noise scenario [2], but fading environment is another limiting factor that results in additional detection performance degradation.

^{[13]}In this paper, the security problem of SISOMR (single input single output with multiple relay-nodes) wireless channel is analyzed and solved in detail.

^{[14]}The design method is derived by the following way, first to consider a design for single input single output(SISO) systems and to modify the control problem for the SISO systems with no time-delays by shifting the outputs with time-delay steps and a design method with no time-delays is applied to the modified systems.

^{[15]}Stability robustness conditions are verified in the frequency domain, while simulations in time domain are carried out to evaluate the controllers and compare their performance along with that of proportional + integral (PI) and single input single output (SISO) QFT controllers designed earlier.

^{[16]}In this paper, a new control method for a class of single input single output nonaffine nonlinear systems is considered using radial basis function (RBF) neural networks (NNs).

^{[17]}In this paper, an analytical model is developed for evaluating the performance of a multi-hop decode and forward (DF) single input single output(SISO) power line communiction(PLC) system in terms of BER.

^{[18]}Considering in a first step of evolution solely a single input single output system the existing stability criterion could be improved in terms of accuracy.

^{[19]}By these complete and simplified models, a step by step method has been proposed to design a single input single output (SISO), second order controller based on roots locus method.

^{[20]}The simulation results show that the bit error rate (BER) performance and the communication distance have been improved than the single input single output (SISO) system.

^{[21]}As for single input single output wire-line and wireless systems, one motivation is to relocate the hardware complexity of the receiver to some extend to the transmitter, Fischer (Precoding and Signal Shaping for Digital Transmission.

^{[22]}Among the many transmission architectures which exploit multiple-antenna at either the transmitter, the receiver, or both, spatial modulation (SM) is a novel and recently proposed multiple-antennas transmission technique which can offer, with a very low system complexity, improved data rates compared to Single Input Single Output (SISO) systems, and robust error performance even in correlated channel environments.

^{[23]}When 6 packets are transmitted in 4 time slots, the proposed adaptive precoding attains about a gain of 4dB at the BER of 10^{-4} in a single input single output Rician fading channel, i.

^{[24]}Accordingly, the single input single output (SISO) intuitionistic fuzzy systems are built.

^{[25]}The converter can work in single input single output, single input dual output, and dual input single output modes.

^{[26]}So this paper investigates the dominant factor among the fraction of block time for energy harvesting or power-splitting ratio in case of outage probabilities and channel capacity for the far user of the considered system with Single Input Single Output (SISO) scheme and Multiple Input Single Output (MISO) scheme as well.

^{[27]}In this paper, the performance of a single input single output FSOC link over $\mathcal{M}$-distribution turbulence fading channel in the presence of misalignment fading (pointing error) is studied.

^{[28]}This work proposes an approach to control continuous-time SISO (Single Input Single Output) time-delay processes subject to output disturbances employing discrete-time PI (Proportional plus Integral) LQR (Linear Quadratic Regulator) controllers.

^{[29]}The simulation results demonstrate that for BICM and BICM-ID the cooperative communication scheme exceeds the single input single output (SISO) technique.

^{[30]}To exclude the non-plasma magnetic perturbation by the external current coils and their secondary eddy currents on the passive stabilizer that may not be easily characterized, the ARX-SISO (autoregressive with exogenous terms-single input single output) method has been introduced in the signal compensation process.

^{[31]}ABSTRACT A method for the identification of single input single output linear systems is presented.

^{[32]}Controlling a single input single output system is very simple but for a multivariable system controlling becomes complex.

^{[33]}ABSTRACT The single input single output (SISO) system with known strong interference is widely used in various occasions.

^{[34]}The results are compared with the results of a Single Input Single Output (SISO)-VLC system.

^{[35]}In this paper, a comparison between different coil systems such as Single Input Single Output (SISO), Parallel Multi Input Single Output (P-MISO) and a Controlled Parallel Multi Input Single Output (CP-MISO) coils systems is carried out.

^{[36]}Coherent detection schemes require full Channel State Information (CSI) at the receiver for Single Input Single Output (SIMO) system.

^{[37]}This paper focuses on the indirect adaptive fuzzy control of Single Input Single Output (SISO) non-linear systems with unknown linearities.

^{[38]}Based on the developed impedance model, the impedance differences between the DPC without PLL and conventional vector control is first revealed, and then the stability influence on DFIG system will be analyzed by using single input single output (SISO) impedance model, especially when DFIG is connected to the weak grid.

^{[39]}The simulation of single input single output (SISO) communication system with spectrum holes is presented.

^{[40]}The results of experiments in the form of B-Scan Image showed that the application of the MIMO system in TWR provides enhanced target detection capabilities compared to the Single Input Single Output (SISO) TWR method.

^{[41]}In order to achieve high data rates and better system performance we extend the single input single output (SISO) system to multiuser/multi input multi output (MIMO).

^{[42]}

## multiple input multiple

Multiple-input multiple-output (MIMO) molecular communication (MC) systems can provide significantly better data rates than single-input single-output (SISO) systems.^{[1]}This paper considers a different approach from the conventional way of maximizing sum rate where the bandwidth is always assumed to be shared evenly among users in a power-constrained single-input single-output (SISO) channel or multiple-input multiple-output (MIMO) channel.

^{[2]}The proposed approximations are of variable-order to achieve the desired accuracy and also have specific parameters using which, multiple-input multiple-output (MIMO) diversity systems can be explicitly analyzed as simply as a single-input single-output (SISO) system.

^{[3]}This work aims to provide a comprehensive state-of-the-art review of the most recent Machine Learning (ML) based AMR methods for Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) systems.

^{[4]}While predominantly studied in single-input single-output (SISO) systems, practical modrec for multiple-input multiple-output (MIMO) communications requires more research attention.

^{[5]}Moreover, by adopting single-input single-output (SISO) rather than multiple-input multiple-output (MIMO) system as before, the MCI radar system with synthetic aperture could be greatly simplified.

^{[6]}The relationships between EE and SE in single-input single-output (SISO), multiple-input multiple-output, and hybrid beamforming structures are first reviewed, where the increase of SE (EE) will unfortunately bring a reduction of EE (SE).

^{[7]}Numerical simulations are provided to validate the model and a capacity evaluation is done considering single input single output (SISO) and different multiple input multiple output (MIMO) configurations.

^{[8]}In this paper, the bit error rate performance of single input single output and multiple input multiple output based FSO system is analyzed and compared.

^{[9]}We consider both SISO (single input single output) and MIMO (Multiple Input Multiple Output) PLC schemes, showing that they are a feasible alternative for in-home PLC applications.

^{[10]}To improve the data transmission rate of the conventional point-to-point single input single output (SISO) visible light communication system, a multiple input multiple output (MIMO) visible light communication system is proposed.

^{[11]}

## input multi output

The methods are studied for not only single-input single-output (SISO) but also multi-input multi-output (MIMO) systems.^{[1]}Both Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) are supported in our testbed.

^{[2]}A reduced-order multi-input multi-output (MIMO) transfer function that contains four single-input single-output (SISO) transfer functions for the weak-grid-tied VSC is first presented.

^{[3]}Although from point of structure view, the system is seen as a single-input single-output system, based on control strategy, it is a multi-input multi-output (MIMO) system.

^{[4]}Based on the gap metric concept, two single-input single-output controllers are used for the longitudinal motion; and one multi-input multi-output for the lateral motion.

^{[5]}

## input single output

To address this critical shortcoming, we propose a novel tensor information channel which extends the current single-input single-output matrix information channel to a more practical multi-input single-output tensor information channel.^{[1]}The ability of single-input single-output (SISO) and dual-input single-output (DISO) digital predistortion (DPD) techniques to linearize the PA arrays is assessed under 5G-candidate 100 MHz orthogonal frequency-division multiplexing (OFDM) test signals.

^{[2]}We propose to use both single-input single-output (SISO), as well as multiple-input single-output (MISO) test cases.

^{[3]}This work focused on the analysis and design of PI + CI controllers and reset controllers in general, for the case of parallel multiple-input single-output (MISO) systems, extending previous design methods developed for the single-input single-output (SISO) case.

^{[4]}

## sliding mode control

This research article presents a process control application of a single-input single-output (SISO) level control system using the combination of fast terminal sliding mode control (FTSMC) and optimization method.^{[1]}We present sufficient conditions to guarantee asymptotic stability of single-input single-output systems driven by integral fuzzy-based sliding mode control.

^{[2]}In this letter, a novel data-driven control algorithm is presented coupling Model-Free Adaptive Control and Sliding Mode Control, which addresses general discrete-time Single-Input Single-Output nonlinear nonaffine systems and is aimed at strengthening standard techniques in the presence of a class of output-dependent perturbations.

^{[3]}5 is replaced by single-input single-output (SISO) radial basis function neural networks (RBFNNs), which are non-linear and continuous functions, thus resulting in adaptive neural sliding mode control (ANSMC).

^{[4]}

## linear time invariant

The results of the development of an approach for the robust pole assignment based on the fulfillment of the Rouche's theorem conditions for a linear time-invariant single-input single-output system with system matrix parametric uncertainty and full-order state observer-based modal control are presented.^{[1]}Here we address the closed-loop stabilization of a single-input single-output (SISO) unstable linear time invariant (LTI) plant model over an additive non-zero mean white noise (AWN) channel located either over the feedback path or the direct path.

^{[2]}This article presents a fairly complete account on various topological and metrical aspects of feedback stabilization for single-input single-output (SISO) continuous and discrete time linear time-invariant (LTI) systems.

^{[3]}

## input multiple output

The proposed system is analyzed and its performance is compared with Single Input Single Output (SISO) FSO system and Single Input Multiple Output (SIMO) FSO system.^{[1]}The presented technique is simulated and tested for up to four multi-paths on each transmit and receive pair of different systems such as single input single output (SISO), single input multiple output (SIMO) or maximal ratio receiver combining (MRRC) and multiple input multiple output (MIMO).

^{[2]}

## strict feedback form

In this paper, the adaptive fuzzy backstepping control problem is considered for a class of single-input single-output (SISO) unknown uncertain nonaffine nonlinear systems in strict-feedback form.^{[1]}The current paper addresses the fuzzy adaptive tracking control via output feedback for single-input single-output (SISO) nonlinear systems in strict-feedback form.

^{[2]}

## single input multiple

The millimeter-wave single-input single-output (SISO) channel and single input multiple output (SIMO) channel are modeled and simulated in the outdoor microcellular scenarios at 28 GHz and 39 GHz based on improved ray tracing method and back propagation (BP) neural network algorithm.^{[1]}The summation of all the losses estimates path loss for single-input single-output (SISO), single-input multiple-output (SIMO), and multiple-input multiple-output (MIMO) antennas low-loss model infrastructure at 900, 1800, and 2100 MHz frequency bands.

^{[2]}

## orthogonal frequency division

In this paper, we investigate physical-layer security for the indoor single-input single-output (SISO) DC-biased optical orthogonal frequency division multiplexing (DCO-OFDM) visible light communication (VLC) wiretap systems.^{[1]}First, we analyze the inputoutput relationship of the single-input single-output (SISO) OTFS based on the orthogonal frequency division multiplexing (OFDM) modem and extend it to massive MIMO-OTFS.

^{[2]}

## adaptive output feedback

In this work, the fuzzy adaptive output feedback control is investigated for single-input single-output (SISO) uncertain nonlinear systems in strict-feedback form.^{[1]}In this paper, an adaptive output feedback fault tolerant control (FTC) based on actuator switching is proposed for a class of single-input single-output (SISO) nonlinear systems with uncertain parameters and possible actuator failures, for which a set of healthy actuators are available as backups.

^{[2]}

## Two Single Input Single Output

The single input dual output (SIDO) converters are efficient than two single input single output (SISO) converters.^{[1]}After estimating and cancelling, the pressure-flow coupling system can be transformed into two single input single output subsystems with the form of cascade integrators.

^{[2]}

## single input single output system

To evaluate the effect of the smoothing parameter the proposed controller is first applied to a single input single output system.^{[1]}Considering in a first step of evolution solely a single input single output system the existing stability criterion could be improved in terms of accuracy.

^{[2]}These differential equations are solved using Laplace Transform technique to build single input single output system models in time domain.

^{[3]}Controlling a single input single output system is very simple but for a multivariable system controlling becomes complex.

^{[4]}