Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,th...Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.展开更多
Variable material screw-based material extrusion(S-MEX)3D printing technology provides a novel approach for fabricating composites with continuous material gradients.Nevertheless,achieving precise alignment between th...Variable material screw-based material extrusion(S-MEX)3D printing technology provides a novel approach for fabricating composites with continuous material gradients.Nevertheless,achieving precise alignment between the process parameters and material compositions is challenging because of fluctuations in the melt rheological state caused by material variations.In this study,an invertible extrusion prediction model for 0-40 wt% short carbon fiber reinforced polyether-ether-ketone(SCF/PEEK)in the S-MEX process was established using an invertible neural network(INN)that demonstrated the capabilities of forward flow rate prediction and inverse process optimization with accuracies of 0.852 and 0.877,respectively.Moreover,a strategy for adjusting the screw speeds using process parameters obtained from the INN was developed to maintain a consistent flow rate during the variable material printing process.Benefiting from uniform flow,the linewidth accuracy was improved by 77%,and the surface roughness was reduced by 51%.Adjusting the process parameters by using an INN offers significant potential for flow rate control and the enhancement of the overall performance of variable material 3D printing.展开更多
Using neural networks for supervised learning means learning a function that maps input <em>x</em> to output <em>y</em>. However, in many applications, the inverse learning is also wanted, <...Using neural networks for supervised learning means learning a function that maps input <em>x</em> to output <em>y</em>. However, in many applications, the inverse learning is also wanted, <em>i.e.</em>, inferring <em>y</em> from <em>x</em>, which requires invertibility of the learning. Since the dimension of input is usually much higher than that of the output, there is information loss in the forward learning from input to output. Thus, creating invertible neural networks is a difficult task. However, recent development of invertible learning techniques such as normalizing flows has made invertible neural networks a reality. In this work, we applied flow-based invertible neural networks as generative models to inverse molecule design. In this context, the forward learning is to predict chemical properties given a molecule, and the inverse learning is to infer the molecules given the chemical properties. Trained on 100 and 1000 molecules, respectively, from a benchmark dataset QM9, our model identified novel molecules that had chemical property values well exceeding the limits of the training molecules as well as the limits of the whole QM9 of 133,885 molecules, moreover our generative model could easily sample many molecules (<em>x</em> values) from any one chemical property value (<em>y</em> value). Compared with the previous method in the literature that could only optimize one molecule for one chemical property value at a time, our model could be trained once and then be sampled any multiple times and for any chemical property values without the need of retraining. This advantage comes from treating inverse molecule design as an inverse regression problem. In summary, our main contributions were two: 1) our model could generalize well from the training data and was very data efficient, 2) our model could learn bidirectional correspondence between molecules and their chemical properties, thereby offering the ability to sample any number of molecules from any <em>y</em> values. In conclusion, our findings revealed the efficiency and effectiveness of using invertible neural networks as generative models in inverse molecule design.展开更多
As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge...As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network watermarking.Leveraging 2D image watermarking technology for 3D scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3D scenes.However,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s robustness.This module restores distorted images through neural network processing before watermark extraction.Additionally,embedding watermarks in each training image enables watermark information extraction from multiple viewpoints.Our proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,respectively.These results demonstrate the efficacy of our scheme in enhancing copyright protection.展开更多
Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit metho...Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue comprehensively.In response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of watermarks.It is just that the information flow is in the opposite direction.Additionally,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse process.This paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video datasets.The results demonstrate its efficacy in extracting watermarking information for copyright protection of NeRV.MarkINeRV represents a pioneering investigation into copyright issues surrounding NeRV.展开更多
The connectedness of the invertibles question for arbitrary nest has been reduced to the case of the lower triangular operators with respect to a fixed orthonormal basis en for n 1. For each f ∈ H∞, let Tf be the To...The connectedness of the invertibles question for arbitrary nest has been reduced to the case of the lower triangular operators with respect to a fixed orthonormal basis en for n 1. For each f ∈ H∞, let Tf be the Toeplitz operator. In this paper we prove that Tf can be connected to the identity through a path in the invertible group of the lower triangular operators if f satisfies certain conditions.展开更多
We study the structure of invertible substitutions on three-letter alphabet. We show that there exists a finite set S of invertible substitutions such that any invertible substitution can be written as I wσ 1σ ...We study the structure of invertible substitutions on three-letter alphabet. We show that there exists a finite set S of invertible substitutions such that any invertible substitution can be written as I wσ 1σ 2…σ k,where I w is the inner automorphism associated with w, and σ j∈ S for 1≤j≤k. As a consequence,M is the matrix of an invertible substitution if and only if it is a finite product of non-negative elementary matrices.展开更多
A logarithm representation of evolution operators is defined. Generators of invertible evolution families are characterized by the logarithm representation. In this article, using the logarithm representation, a conce...A logarithm representation of evolution operators is defined. Generators of invertible evolution families are characterized by the logarithm representation. In this article, using the logarithm representation, a concept of evolution operators without satisfying the semigroup property is introduced. In conclusion the existence of alternative infinitesimal generator is clarified.展开更多
An embedding from a group algebra to a matrix algebra is given in this paper. By using it, a criterion for an invertible element in a group algebra is proven.
The large spatial/temporal/frequency scale of geoscience and remote-sensing datasets causes memory issues when using convolutional neural networks for(sub-)surface data segmentation.Recently developed fully reversible...The large spatial/temporal/frequency scale of geoscience and remote-sensing datasets causes memory issues when using convolutional neural networks for(sub-)surface data segmentation.Recently developed fully reversible or fully invertible networks can mostly avoid memory limitations by recomputing the states during the backward pass through the network.This results in a low and fixed memory requirement for storing network states,as opposed to the typical linear memory growth with network depth.This work focuses on a fully invertible network based on the telegraph equation.While reversibility saves the major amount of memory used in deep networks by the data,the convolutional kernels can take up most memory if fully invertible networks contain multiple invertible pooling/coarsening layers.We address the explosion of the number of convolutional kernels by combining fully invertible networks with layers that contain the convolutional kernels in a compressed form directly.A second challenge is that invertible networks output a tensor the same size as its input.This property prevents the straightforward application of invertible networks to applications that map between different input-output dimensions,need to map to outputs with more channels than present in the input data,or desire outputs that decrease/increase the resolution compared to the input data.However,we show that by employing invertible networks in a non-standard fashion,we can still use them for these tasks.Examples in hyperspectral land-use classification,airborne geophysical surveying,and seismic imaging illustrate that we can input large data volumes in one chunk and do not need to work on small patches,use dimensionality reduction,or employ methods that classify a patch to a single central pixel.展开更多
This paper presents in organized form a number of results that have appeared in the literature in the last two decades,concerning the design of control laws for multi-input multi-output nonlinear systems,with emphasis...This paper presents in organized form a number of results that have appeared in the literature in the last two decades,concerning the design of control laws for multi-input multi-output nonlinear systems,with emphasis on the problem of stabilizing an equilibrium,and addresses,at a broad level generality,systems that are invertible from an input-output viewpoint.展开更多
Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly in...Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly invertible finite automaton M with delay 2 satisfying the properties mentioned in this paper, two weakly invertible finite automata with delay 1 are constructed such that M is equivalent to a sub-finite-automaton of the composition of those two. So a method to decompose this a kind of weakly invertible finite automata with delay 2 is presented.展开更多
By introducing the notion of 'prime substitution' it is shown that the set of invertible substitutions over an alphabet of more than three letters is not finitely generated. Some examples are given.
Inclines are the additively idempotent semirings in which products are less than or equal to either factor. In this paper, some necessary and sufficient conditions for a matrix over L to be invertible are given, where...Inclines are the additively idempotent semirings in which products are less than or equal to either factor. In this paper, some necessary and sufficient conditions for a matrix over L to be invertible are given, where L is an incline with 0 and 1. Also it is proved that L is an integral incline if and only if GLn（L） = PLn （L） for any n （n 〉 2）, in which GLn（L） is the group of all n × n invertible matrices over L and PLn（L） is the group of all n × n permutation matrices over L. These results should be regarded as the generalizations and developments of the previous results on the invertible matrices over a distributive lattice.展开更多
In this paper we obtain a criterion under which the bijectivity of the canonical morphism of a weak Galois extension associated to a weak invertible entwining structure is equivalent to the existence of a strong conne...In this paper we obtain a criterion under which the bijectivity of the canonical morphism of a weak Galois extension associated to a weak invertible entwining structure is equivalent to the existence of a strong connection form. Also we obtain an explicit formula for a strong connection under equivariant projective conditions or under coseparability conditions.展开更多
Converting subsurface offset domain common image gathers(ODCIGs)to angle domain common image gathers(ADCIGs)through a Radon Transform(RT)in either the spatial or wavenumber domain is efficient and valid except for the...Converting subsurface offset domain common image gathers(ODCIGs)to angle domain common image gathers(ADCIGs)through a Radon Transform(RT)in either the spatial or wavenumber domain is efficient and valid except for the distortion of both frequency spectrum and amplitude versus angle(AVA)effect.This paper presents two modifications to the existing method to keep the frequency spectrum of the resultant ADCIGs the same as the input data and to preserve the relative amplitudes.The spectrum invariance is achieved by replacing the conventional RT or slant slack by an invertible RT.Amplitude preservation is obtained by applying an amplitude correction factor in the angle domain.Tests on both synthetic and field datasets validate the accuracy of these modifications.展开更多
The introduction of two-dimensional(2D)perovskite layers on top of three-dimensional(3D)perovskite films enhances the performance and stability of perovskite solar cells(PSCs).However,the electronic effect of the spac...The introduction of two-dimensional(2D)perovskite layers on top of three-dimensional(3D)perovskite films enhances the performance and stability of perovskite solar cells(PSCs).However,the electronic effect of the spacer cation and the quality of the 2D capping layer are critical factors in achieving the required results.In this study,we compared two fluorinated salts:4-(trifluoromethyl)benzamidine hydrochloride(4TF-BA·HCl)and 4-fluorobenzamidine hydrochloride(4F-BA·HCl)to engineer the 3D/2D perovskite films.Surprisingly,4F-BA formed a high-performance 3D/2D heterojunction,while4TF-BA produced an amorphous layer on the perovskite films.Our findings indicate that the balanced intramolecular charge polarization,which leads to effective hydrogen bonding,is more favorable in 4F-BA than in 4TF-BA,promoting the formation of a crystalline 2D perovskite.Nevertheless,4TF-BA managed to improve efficiency to 24%,surpassing the control device,primarily due to the natural passivation capabilities of benzamidine.Interestingly,the devices based on 4F-BA demonstrated an efficiency exceeding 25%with greater longevity under various storage conditions compared to 4TF-BA-based and the control devices.展开更多
Some new characterizations of nonnegative Hamiltonian operator matrices are given. Several necessary and sufficient conditions for an unbounded nonnegative Hamiltonian operator to be invertible are obtained, so that t...Some new characterizations of nonnegative Hamiltonian operator matrices are given. Several necessary and sufficient conditions for an unbounded nonnegative Hamiltonian operator to be invertible are obtained, so that the main results in the previously published papers are corollaries of the new theorems. Most of all we want to stress the method of proof. It is based on the connections between Pauli operator matrices and nonnegative Hamiltonian matrices.展开更多
Given two closed, in general unbounded, operators A and C, we investigate the left invertible completion of the partial operator matrix A ？ 0 C. Based on the space decomposition technique, the alternative sufficient ...Given two closed, in general unbounded, operators A and C, we investigate the left invertible completion of the partial operator matrix A ？ 0 C. Based on the space decomposition technique, the alternative sufficient and necessary conditions are given according to whether the dimension of R（A）⊥ is finite or infinite.As a direct consequence, the perturbation of left spectra is further presented.展开更多
Complementary inverter is the basic unit for logic circuits,but the inverters based on full oxide thin-film transistors(TFTs)are still very limited.The next challenge is to realize complementary inverters using homoge...Complementary inverter is the basic unit for logic circuits,but the inverters based on full oxide thin-film transistors(TFTs)are still very limited.The next challenge is to realize complementary inverters using homogeneous oxide semiconduc-tors.Herein,we propose the design of complementary inverter based on full ZnO TFTs.Li-N dual-doped ZnO(ZnO:(Li,N))acts as the p-type channel and Al-doped ZnO(ZnO:Al)serves as the n-type channel for fabrication of TFTs,and then the complemen-tary inverter is produced with p-and n-type ZnO TFTs.The homogeneous ZnO-based complementary inverter has typical volt-age transfer characteristics with the voltage gain of 13.34 at the supply voltage of 40 V.This work may open the door for the development of oxide complementary inverters for logic circuits.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.62202234,62401270)the China Postdoctoral Science Foundation(No.2023M741778)the Natural Science Foundation of Jiangsu Province(Nos.BK20240706,BK20240694).
文摘Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.
基金supported by National Natural Science Foundation of China(Grant Nos.12202547,62461160259)Shaanxi Province Qingchuangyuan“Scientist and Engineering”Team Construction Project(Grant Nos.2022KXJ-102,2022KXJ-106)+1 种基金Fundamental Research Funds for the Central UniversitiesProgram for Innovation Team of Shaanxi Province(Grant No.2023-CX-TD-17).
文摘Variable material screw-based material extrusion(S-MEX)3D printing technology provides a novel approach for fabricating composites with continuous material gradients.Nevertheless,achieving precise alignment between the process parameters and material compositions is challenging because of fluctuations in the melt rheological state caused by material variations.In this study,an invertible extrusion prediction model for 0-40 wt% short carbon fiber reinforced polyether-ether-ketone(SCF/PEEK)in the S-MEX process was established using an invertible neural network(INN)that demonstrated the capabilities of forward flow rate prediction and inverse process optimization with accuracies of 0.852 and 0.877,respectively.Moreover,a strategy for adjusting the screw speeds using process parameters obtained from the INN was developed to maintain a consistent flow rate during the variable material printing process.Benefiting from uniform flow,the linewidth accuracy was improved by 77%,and the surface roughness was reduced by 51%.Adjusting the process parameters by using an INN offers significant potential for flow rate control and the enhancement of the overall performance of variable material 3D printing.
文摘Using neural networks for supervised learning means learning a function that maps input <em>x</em> to output <em>y</em>. However, in many applications, the inverse learning is also wanted, <em>i.e.</em>, inferring <em>y</em> from <em>x</em>, which requires invertibility of the learning. Since the dimension of input is usually much higher than that of the output, there is information loss in the forward learning from input to output. Thus, creating invertible neural networks is a difficult task. However, recent development of invertible learning techniques such as normalizing flows has made invertible neural networks a reality. In this work, we applied flow-based invertible neural networks as generative models to inverse molecule design. In this context, the forward learning is to predict chemical properties given a molecule, and the inverse learning is to infer the molecules given the chemical properties. Trained on 100 and 1000 molecules, respectively, from a benchmark dataset QM9, our model identified novel molecules that had chemical property values well exceeding the limits of the training molecules as well as the limits of the whole QM9 of 133,885 molecules, moreover our generative model could easily sample many molecules (<em>x</em> values) from any one chemical property value (<em>y</em> value). Compared with the previous method in the literature that could only optimize one molecule for one chemical property value at a time, our model could be trained once and then be sampled any multiple times and for any chemical property values without the need of retraining. This advantage comes from treating inverse molecule design as an inverse regression problem. In summary, our main contributions were two: 1) our model could generalize well from the training data and was very data efficient, 2) our model could learn bidirectional correspondence between molecules and their chemical properties, thereby offering the ability to sample any number of molecules from any <em>y</em> values. In conclusion, our findings revealed the efficiency and effectiveness of using invertible neural networks as generative models in inverse molecule design.
基金supported by the National Natural Science Foundation of China,with Fund Numbers 62272478,62102451the National Defense Science and Technology Independent Research Project(Intelligent Information Hiding Technology and Its Applications in a Certain Field)and Science and Technology Innovation Team Innovative Research Project Research on Key Technologies for Intelligent Information Hiding”with Fund Number ZZKY20222102.
文摘As neural radiance fields continue to advance in 3D content representation,the copyright issues surrounding 3D models oriented towards implicit representation become increasingly pressing.In response to this challenge,this paper treats the embedding and extraction of neural radiance field watermarks as inverse problems of image transformations and proposes a scheme for protecting neural radiance field copyrights using invertible neural network watermarking.Leveraging 2D image watermarking technology for 3D scene protection,the scheme embeds watermarks within the training images of neural radiance fields through the forward process in invertible neural networks and extracts them from images rendered by neural radiance fields through the reverse process,thereby ensuring copyright protection for both the neural radiance fields and associated 3D scenes.However,challenges such as information loss during rendering processes and deliberate tampering necessitate the design of an image quality enhancement module to increase the scheme’s robustness.This module restores distorted images through neural network processing before watermark extraction.Additionally,embedding watermarks in each training image enables watermark information extraction from multiple viewpoints.Our proposed watermarking method achieves a PSNR(Peak Signal-to-Noise Ratio)value exceeding 37 dB for images containing watermarks and 22 dB for recovered watermarked images,as evaluated on the Lego,Hotdog,and Chair datasets,respectively.These results demonstrate the efficacy of our scheme in enhancing copyright protection.
基金supported by the National Natural Science Foundation of China,with Fund Numbers 62272478,62102451the National Defense Science and Technology Independent Research Project(Intelligent Information Hiding Technology and Its Applications in a Certain Field)and Science and Technology Innovation Team Innovative Research Project“Research on Key Technologies for Intelligent Information Hiding”with Fund Number ZZKY20222102.
文摘Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue comprehensively.In response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of watermarks.It is just that the information flow is in the opposite direction.Additionally,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse process.This paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video datasets.The results demonstrate its efficacy in extracting watermarking information for copyright protection of NeRV.MarkINeRV represents a pioneering investigation into copyright issues surrounding NeRV.
基金The NSF (10971079) of Chinathe Basic Research Foundation (201001001,201103194) of Jilin University
文摘The connectedness of the invertibles question for arbitrary nest has been reduced to the case of the lower triangular operators with respect to a fixed orthonormal basis en for n 1. For each f ∈ H∞, let Tf be the Toeplitz operator. In this paper we prove that Tf can be connected to the identity through a path in the invertible group of the lower triangular operators if f satisfies certain conditions.
文摘We study the structure of invertible substitutions on three-letter alphabet. We show that there exists a finite set S of invertible substitutions such that any invertible substitution can be written as I wσ 1σ 2…σ k,where I w is the inner automorphism associated with w, and σ j∈ S for 1≤j≤k. As a consequence,M is the matrix of an invertible substitution if and only if it is a finite product of non-negative elementary matrices.
文摘A logarithm representation of evolution operators is defined. Generators of invertible evolution families are characterized by the logarithm representation. In this article, using the logarithm representation, a concept of evolution operators without satisfying the semigroup property is introduced. In conclusion the existence of alternative infinitesimal generator is clarified.
文摘An embedding from a group algebra to a matrix algebra is given in this paper. By using it, a criterion for an invertible element in a group algebra is proven.
文摘The large spatial/temporal/frequency scale of geoscience and remote-sensing datasets causes memory issues when using convolutional neural networks for(sub-)surface data segmentation.Recently developed fully reversible or fully invertible networks can mostly avoid memory limitations by recomputing the states during the backward pass through the network.This results in a low and fixed memory requirement for storing network states,as opposed to the typical linear memory growth with network depth.This work focuses on a fully invertible network based on the telegraph equation.While reversibility saves the major amount of memory used in deep networks by the data,the convolutional kernels can take up most memory if fully invertible networks contain multiple invertible pooling/coarsening layers.We address the explosion of the number of convolutional kernels by combining fully invertible networks with layers that contain the convolutional kernels in a compressed form directly.A second challenge is that invertible networks output a tensor the same size as its input.This property prevents the straightforward application of invertible networks to applications that map between different input-output dimensions,need to map to outputs with more channels than present in the input data,or desire outputs that decrease/increase the resolution compared to the input data.However,we show that by employing invertible networks in a non-standard fashion,we can still use them for these tasks.Examples in hyperspectral land-use classification,airborne geophysical surveying,and seismic imaging illustrate that we can input large data volumes in one chunk and do not need to work on small patches,use dimensionality reduction,or employ methods that classify a patch to a single central pixel.
文摘This paper presents in organized form a number of results that have appeared in the literature in the last two decades,concerning the design of control laws for multi-input multi-output nonlinear systems,with emphasis on the problem of stabilizing an equilibrium,and addresses,at a broad level generality,systems that are invertible from an input-output viewpoint.
文摘Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly invertible finite automaton M with delay 2 satisfying the properties mentioned in this paper, two weakly invertible finite automata with delay 1 are constructed such that M is equivalent to a sub-finite-automaton of the composition of those two. So a method to decompose this a kind of weakly invertible finite automata with delay 2 is presented.
文摘By introducing the notion of 'prime substitution' it is shown that the set of invertible substitutions over an alphabet of more than three letters is not finitely generated. Some examples are given.
基金National Natural Science Foundation of China （60174013） Research Foundation for Doctoral Program of Higher Education （20020027013）+1 种基金 Science and Technology Key Project Foundation of Ministry of Education （03184） Major State Basic Research Development Program of China （2002CB312200）
文摘Inclines are the additively idempotent semirings in which products are less than or equal to either factor. In this paper, some necessary and sufficient conditions for a matrix over L to be invertible are given, where L is an incline with 0 and 1. Also it is proved that L is an integral incline if and only if GLn（L） = PLn （L） for any n （n 〉 2）, in which GLn（L） is the group of all n × n invertible matrices over L and PLn（L） is the group of all n × n permutation matrices over L. These results should be regarded as the generalizations and developments of the previous results on the invertible matrices over a distributive lattice.
基金Supported by Ministerio de Educació n, Xunta de Galicia and by FEDER (Grant Nos. MTM2010-15634,MTM2009-14464-C02-01, PGIDT07PXB322079PR)
文摘In this paper we obtain a criterion under which the bijectivity of the canonical morphism of a weak Galois extension associated to a weak invertible entwining structure is equivalent to the existence of a strong connection form. Also we obtain an explicit formula for a strong connection under equivariant projective conditions or under coseparability conditions.
文摘Converting subsurface offset domain common image gathers(ODCIGs)to angle domain common image gathers(ADCIGs)through a Radon Transform(RT)in either the spatial or wavenumber domain is efficient and valid except for the distortion of both frequency spectrum and amplitude versus angle(AVA)effect.This paper presents two modifications to the existing method to keep the frequency spectrum of the resultant ADCIGs the same as the input data and to preserve the relative amplitudes.The spectrum invariance is achieved by replacing the conventional RT or slant slack by an invertible RT.Amplitude preservation is obtained by applying an amplitude correction factor in the angle domain.Tests on both synthetic and field datasets validate the accuracy of these modifications.
基金supported by the National Key Research and Development Programs-Intergovernmental International Cooperation in Science and Technology Innovation Project(Grant No.2022YFE0118400)the Natural Science Foundation of Hunan Province(2023JJ50132)+1 种基金Shenzhen Science and Technology Innovation Committee(Grants Nos.JCYJ20220818100211025,and KCXST20221021111616039)Shenzhen Science and Technology Program(No.20231128110928003)。
文摘The introduction of two-dimensional(2D)perovskite layers on top of three-dimensional(3D)perovskite films enhances the performance and stability of perovskite solar cells(PSCs).However,the electronic effect of the spacer cation and the quality of the 2D capping layer are critical factors in achieving the required results.In this study,we compared two fluorinated salts:4-(trifluoromethyl)benzamidine hydrochloride(4TF-BA·HCl)and 4-fluorobenzamidine hydrochloride(4F-BA·HCl)to engineer the 3D/2D perovskite films.Surprisingly,4F-BA formed a high-performance 3D/2D heterojunction,while4TF-BA produced an amorphous layer on the perovskite films.Our findings indicate that the balanced intramolecular charge polarization,which leads to effective hydrogen bonding,is more favorable in 4F-BA than in 4TF-BA,promoting the formation of a crystalline 2D perovskite.Nevertheless,4TF-BA managed to improve efficiency to 24%,surpassing the control device,primarily due to the natural passivation capabilities of benzamidine.Interestingly,the devices based on 4F-BA demonstrated an efficiency exceeding 25%with greater longevity under various storage conditions compared to 4TF-BA-based and the control devices.
基金Supported by Natural Science Foundation of China(Grant Nos.11361034,11371185,11101200)Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20111501110001)+1 种基金Major Subject of Natural Science Foundation of Inner Mongolia of China(Grant No.2013ZD01)Natural Science Foundation of Inner Mongolia of China(Grant No.2012MS0105)
文摘Some new characterizations of nonnegative Hamiltonian operator matrices are given. Several necessary and sufficient conditions for an unbounded nonnegative Hamiltonian operator to be invertible are obtained, so that the main results in the previously published papers are corollaries of the new theorems. Most of all we want to stress the method of proof. It is based on the connections between Pauli operator matrices and nonnegative Hamiltonian matrices.
基金partially supported by the Natural Science Foundation of China(Nos.11461049 and 11371185)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20111501110001)+3 种基金the ‘Chunhui Program’ of the Ministry of Education of China(No.Z2009-1-01010)the Major Program of the National Natural Science Foundation of Inner Mongolia(No.2013ZD01)the National Science Foundation for Fostering Distinguished Young Scholars of Inner Mongolia(No.2013JQ01)the Program for Young Talents of Science and Technology in Universities of Inner Mongolia(No.NJYT-12-B06)
文摘Given two closed, in general unbounded, operators A and C, we investigate the left invertible completion of the partial operator matrix A ？ 0 C. Based on the space decomposition technique, the alternative sufficient and necessary conditions are given according to whether the dimension of R（A）⊥ is finite or infinite.As a direct consequence, the perturbation of left spectra is further presented.
基金supported by Zhejiang Provincial Natural Science Foundation of China(No.LZ24E020001).
文摘Complementary inverter is the basic unit for logic circuits,but the inverters based on full oxide thin-film transistors(TFTs)are still very limited.The next challenge is to realize complementary inverters using homogeneous oxide semiconduc-tors.Herein,we propose the design of complementary inverter based on full ZnO TFTs.Li-N dual-doped ZnO(ZnO:(Li,N))acts as the p-type channel and Al-doped ZnO(ZnO:Al)serves as the n-type channel for fabrication of TFTs,and then the complemen-tary inverter is produced with p-and n-type ZnO TFTs.The homogeneous ZnO-based complementary inverter has typical volt-age transfer characteristics with the voltage gain of 13.34 at the supply voltage of 40 V.This work may open the door for the development of oxide complementary inverters for logic circuits.
