Introduction to Soft Decision

It is a tightly integrated method that passes renormalized source word posterior distributions as a soft decision instead of one-hot vectors and enables backpropagation.

Hierarchical mixture of experts is a hierarchically gated model that defines a soft decision tree where leaves correspond to experts and decision nodes correspond to gating models that softly choose between its children, and as such, the model defines a soft hierarchical partitioning of the input space.

The designed receiver is based on deep neural network(DNN) in deep learning, which consists of a layer of DNN and soft decision.

The Min-Sum decoder has comparatively fewer FPGA resources than other decoders for soft decisions.

The detection efficiency of the NN receiver is attributed to a key parameter entitled as an optimal average cost function which is formulated from the soft decision statistics that is reached by the NN receiver in 3000 training epochs owing to the prudent selection of all hyper-parameters.

On the other hand, fully utilizing the potential of soft decision based codes demands higher precision memory sensing, which introduces a trade-off between the read latency and the error probability.

Additionally, the proposed scheme is compared with several other CSS schemes such as simple DE, simple BTA, maximum gain combination (MGC), particle swarm optimization (PSO), genetic algorithm (GA), and K-nearest neighbor (KNN) algorithm-based soft decision fusion (SDF) schemes to validate its effectiveness.

The paper considers distributed detection problem basis on using soft decision scheme both in the local sensors and in the fusion center (FC).

It is shown that the use of soft decision algorithms in fusion center has a better performance than hard decision algorithms.

This paper investigates digital equalization for PON with respect to performance with soft decision error correction decoding.

In our 50-Gbaud PAM4 experiment, with 60% unlabeled data, the semi-supervised VNLE based on the soft decision (SD) and Lasso demonstrates up to 3-dB sensitivity gain at the BER threshold of 4.

Others are based on soft decisions that require multiple reads for each flash memory cell, leading to significant memory throughput degradation.

The proposed scheme exchanges log-likelihood ratios (LLRs) as soft decision values between the LoRa demodulator and the Hamming decoder to improve the signal detection capability while obtaining the iterative gain.

We propose a hierarchical differentiable neural regression model, Soft Decision Tree Regressor (SDTR).

Simulations also confirm compatibility of GCH with either hard or soft decision decoding methods.

belief propagation algorithm, sum product algorithm and minimum sum algorithm as examples from soft decision.

The soft decision decoding scheme is exploited by high bit-rate users to decode MPPM signals, which could fundamentally eliminate the detrimental effect of EP; the scheme is also easier and faster to execute compared with the conventional SIC decoding scheme.

The collisions and exhaustion attacks are detected based on a soft decision-based algorithm.

The proposed design changes the scrambling operation, and replaces the hard decoding of BPSK modulation symbols with soft decision decoding.

Drawing from soft decision aid theories, we develop a descriptive model of planning based on multiple partial interlinked decisions and explore its consequences to the understanding of planning and its practice.

Soft decision receiver is attractive for the reason that the performance gains result in significant transmitting energy reduction.

However, low-complexity demodulation for SC-GSM signals with near-optimal performance is challenging, especially in soft decision making.

Our proposed IPS-OCSVM framework realizes QoE anomaly detection through soft decision and can easily fine-tune the anomaly detection ability on demand.

, Fuzzy soft matrix theory and its application in decision making, Iranian Journal of Fuzzy Systems, 2012, 9(1), 109-119] calismasinda verilen bulanik esnek maks-min karar verme metodu, Enginoglu ve Memis [A configuration of some soft decision-making algorithms via -matrices, Cumhuriyet Science Journal, 2018, 39(4), 871-881] tarafindan bulanik parametreli bulanik esnek matrisler ( -matrisler) yoluyla orijinaline sadik kalacak bicimde yapilandirildi.

Bit error rate performance evaluation of the implemented hard and soft decision decoding have been carried out by varying trellis depth and soft quantization bits.

Nevertheless, directly exploiting LDPC codes introduces a concern about decoding latency because of their iterative decoding in the soft decision process.

First deals with the theoretical foundations of cognitive radio and the different techniques for sensing in cognitive networks, presenting decision schemes and conventional detection of the cooperative spectrum, the Hard decision and Soft decision methods and finally, an evaluation of the rules of cooperative sensing in real scenarios.

To mitigate these two specific distortions in VCSEL-based link, a k-means assisted PAM-4 signal receiver including equalization and soft decision (SD) is proposed.

In addition, we propose a data detection scheme based on a soft decision to improve the reliability.

Finally, the performance improvement due to the soft decision gain can be obtained by using polar codes rather than using RS codes as outer codes of the concatenated codes.

In this paper, we propose an approach to defend against adversarial examples with soft decision trees embedding.

We consider both hard and soft decision combining in our analysis.

The vector is further utilized in the soft decision schemes that assign appropriate weight to the reports of cooperative users to take a global decision.

Then the SN will give a final judgement based on the soft decision fusion rule.

This paper outline different techniques to mitigate the damaging effects of the false sensing in Soft Decision Fusion (SDF) schemes using One-to-Many Sensing-Distances and Z-Score.

Through the MAP method, the absolute value of the posterior probability ratio is regarded as the soft decision output, the code is used to obtain the error position and the transmission error of the intelligent navigation information is controlled, so that the design of the GIS intelligent navigation information control system for MAV is completed.

A likelihood ratio estimation method based on K-means clustering is proposed and experimentally demonstrated for soft decision of PAM4 to mitigate the level nonlinearity and level-dependent noise.

In the last step, a soft decision method is applied to determine the target location from the candidates.

To cope with this problem, a soft decision control strategy-based iterative CE (SDC-ICE) method is proposed in this paper.

An expression for soft decisions is obtained for incoherent demodulation of signals with m-digit frequency-shift keying in radio communication systems with character frequency hopping in the presence of additional noise with unknown intensity in the frequency channels of the system.

Specifically, the proposed method subtracts the estimated ITI signal (generated based on the soft decision obtained from a decoder for each turbo iteration) from the original readback signal during the turbo decoding process.

The resulting detection scheme therefore outputs, by design, soft decisions under a regularized proximal splittable formulation via the alternating direction method of multipliers (ADMM), facilitating the integration with further coding schemes.

By exploiting such coupled relation, the soft decision optimization method is proposed in this paper to estimate the fundamental matrix and find the inlier correspondence set together.

In this work; however, we propose a soft decision output decoding algorithm of a rate-5/6 constructive ITI (CITI) code to utilize it in an iterative decoding process.

Probabilistic approaches derived from the Bayesian iteration can provide the soft decision for achieving the near-optimal performance and some other benefits such as combination of detection and channel decoding.

In the proposed technique, standard square quadrature amplitude modulation (QAM) constellations are used instead of HQAM so that the QAM mapper at the transmitter side and the soft decision calculation at the receiver side remain unchanged, but the UEP benefit of HQAM is retained.

This study deals with the performance of the soft decision decoder for low-density parity-check codes over impulsive noise channels.

The proposed scheme of Flower Pollination Algorithm (FPA) intelligently finds optimum weighting coefficients against cooperative users' information and utilizes these weights in the global decision of the Soft Decision Fusion (SDF).

Hard and Soft decision detection are usually employed at the fusion center (FC) to detect the presence or absence of the primary user (PU).

Finally, a nonmaximal suppression method based on a soft decision function is proposed to solve the overlap problem of detection boxes.

We show in this paper that the random access (RA) performance of SUCRe can be improved by replacing the hard decision retransmission rule by a soft decision one, so that each user decides to retransmit or not its pilot sequence with a suitable probability.

Because SI very important at receiver, convolutional code with Viterbi-Soft Decision Decoding (V-SDD) is used to protect it against channel distortion.

In massive multiple-input multiple-output (MIMO) crowded networks, the random access (RA) performance of strongest-user collision resolution (SUCRe) protocol can be improved by replacing the hard decision retransmission rule by a soft decision one, so that each user equipment (UE) decides to retransmit or not its pilot sequence with a suitable probability.

The belief propagation (BP) algorithm is a commonly used soft decision decoding algorithm.

The first one is related to hard decision family while the last two types are the soft decision that follows the sum-product algorithm.

Implementation of soft decision speech presence probability with fixed prior ensure that the estimator to be unbiased.

In this paper, we propose a secure fusion strategy which adopts “soft decision” method and can distinguish malicious users and honest users under any distribution of sensing reports using maximum mean discrepancy (MMD).

A soft decision logarithmic likelihood ratio (LLR) based detector is also conceived.

A soft decision mechanism has been implemented to detect collision and exhaus-tion attacks.

These results are verified by simulations, considering terminated convolutional codes with different coding rates, minimum mean-squared error linear equalization (MMSE-LE) and soft decision decoding.