|
Title |
Authors |
Publisher |
![](/Portals/DSWeb/EasyGalleryImages/2/1481/Roberts_ODE.jpg) |
Ordinary Differential Equations: Applications, Models, and Computing |
C. Roberts |
CRC Press |
![](/Portals/DSWeb/EasyGalleryImages/2/1481/Lynch_DSMathematica.jpg) |
Dynamical Systems with Applications Using Mathematica (2nd Edition) |
S. Lynch |
Springer |
![](/Portals/DSWeb/EasyGalleryImages/2/1481/BonkMeyer_ThurstonMaps.jpg) |
Expanding Thurston Maps |
M. Bonk, D. Meyer |
AMS |
![](/Portals/DSWeb/EasyGalleryImages/2/1481/JohnsonMaddenSahin_DiscoDS.jpg) |
Discovering Discrete Dynamical Systems |
A. Johnson, K. Madden, A. Sahin |
AMS |
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SCdMg1BMchsbPg4UZagsnwdw0bMBUlJ0Fh4Etl7t8Wm7NohDDJtGmpqPo0H13PYeIqgSaMpJOLSAaToyIvekRRZrvWX62J8QEfmxJpKCaIElfMbkUBrQiYMElwDFMp7xWfFbNZQ8P3BHwH3cwpo3TdtAl9nyjOEYRinD7YPlnlPYS8NgNfydZD+HUabRiAs9Kf/z8kUwXytHvD+Ygbf4nMau0h744TxOvKKFATq0ItQosj3GRw5aQ5RAE56DJ1oYbBNU9SEEtPPU6JwwjTtsA08MMAzTWVZb/UQ6w+u6anBmVTE0+SwWt8EndIvQcV7VxYhu/glJvpa4bBr0DeWtl57gUX/BDRKZlRTjRRb+Q3zQJJ4hOLzDuUgqTSQyqe+kpauOA9vRuZ+AgbSGWQEzcFGQZl7U/ERTQ1S1RhiY6p55SdhpkzVeP3srjgS4E8uD0viHfxTSYlDE64cUy4ON2wmaIC2RYSGnTJ28KANPQRipGpspakiCYtliWlPi+4KK2mi2H2EHkylqn0EL4Wx0TCc8W3xJFpeUDse+i2jSGG46Jf1g1SoXIx7/UDdDMbKC8qwvnbIVU7H+HSX4NpuBdvs/yGJFQgp/EwS3UdzUjQkgjDEuOVFK/TRBRgIu8myZAFTLGsJ3dp6SVEC9TMbshDTMdUhuFdv40p+jUxZk5CUrGT03QiceHxurilEqmwFWL0IasVwpWG1Hvw6zeGDuHJvVWHjTHP/x7yMgWyNlTO1AmVYZCGaZv43Yjleh3XdZgsjqAPwTibAg9rOCnTYH5NLP4lDtX1VRaXl5gYG2NifEr1JhlGRYRstlqsr60xuyVTJDmmgcg7w64h7H9YdBWeLSwMJtlsGjQ4+ZC27tdWMhz0EUFffPS6EIW4cZHfvf8gp9eWiOKQRKQCe4TQP4PWbrM/rPDdxVVlRF1PxPvpBFWzynqS4hsmnrYO+jqNqEFqd6jZGrWoTkMP8WVZv7tAYpTYb3l854Vlqp2EsBlCocOZM4v8o09+hmq7y3efq+OnPm/9Z5+kulbnTCvk4eV1fGMcTYxgWs/g2y6an5Bo+pCPDM7Dai0kOfgzLI2EK/MFmZlu/PQXUge3Sz9UqE58RoT+dGpepGZnkZmnHbhE9ZRCZR5TH+cbX3gA3Whx89wspjFGrRMRB2M4I1DvrqOHM4RRQGoUiBp12laB0XwBah0lkgVTV3Ho2VNM7JpEz61xLAopuWNM+ybb9s3xoeldGNUzokjFtix+/+P/nnzjCe59cj/7F1bZ9r49tOoB+2Z20bGLdGOTkWTwHEB1+2EsoV/1l/g9jMoVu3iJeano337uBT717afQI5+xLXk++oEP88cP3Mf0bIX5EYOz8Sj//cCjlP0i/+YDP82JM8f4w+8+h2OldJIif/Br7+U3/tWnuHrM4iduvpPDz32f7xw4wNvvfA/v37KXxZU1vn3oYfzFr/JPP/JhxkoLfOrPv8j//nM/RVe5EJv81sf+Mf/lQ2/i4cPHOXisy/f2Pcq/+PTX+Mrv/SbPnzrO5/76a/ybD//Cy6neFU0zhDle/h2+l7IlN8lHf+nDHHr6NFsih//jve/jHdfcwm033cn3Vhb5vfe8n622xdcPHeexRpe777iD99z+JorODE67xkia5zW79vGavTfwK+/5u/z63/01PnHfvTS6NUp5g7/3M+/iPe98L59+5BGSOKXr+8rcLJfLE6WB6u4yPrz2J27kzbe8jruv38Otr7ubx55doLVeZ/feHZevyCsQ42WDLHKrm9OYqqR4pk2atHHjGsWixdLZZbRWk0NrD3FtUaPkObQDnV2TLhMzNg2ZJpt1tJEcO67ZTi3t8t+/+RXchRUabkCsh9g2zGoG+2amOFo/hWa7BGGkpAzdtNT6i/BNU9OpRF3MqEm5W+Oea3bxwMNP06h53Ll99hWA8PKveNkgm4aN4weUvSYj+Um0ZgOzXseIDKycw1SlRHl0knf91M9z4zW7iZwAtxtS9GO8ahfTsUkaXYpGjkcffhZCk2v2zBO4GmUtT2wVaaupfEJe7H4NmWkapElKs9lCT00MGdw0HVNLid0IzbB43ZYJnlte4/GFFtdvmbw8Aq9AjJfNk0Ve9fI6LRfONBowNUE6Nc5jzy/wc9fu5PDJI+y8aTfbbJ2r0jbTXouvPXGQCSul6YzjVZfRJiZZCQMalkOUL3OksQS1Ko5f4rkTKyQjNicefYR3vf5ukd/QuxqW6ZJqGpZeoNFsEkQJkeNyoH6Qle4Wto5YxFu28rxnUT63svIKILnJK4zf+Z3f+R28R4aKLCKOJOJM7rrUI5+rizrFUp7JkQpzxVn2Tk0yETfYtXOGea1JUGvD6Di/ctedfONbT/LUylFu2jHL3r3b8Zt1WqUxio2TvP32t1NZeJ4bd21j12SB0/ufJnV1XrdtG5V988yM2DTPnGTffJE33HoNhmVR0Bps3zWHY9YZm53kutGQ8clRrs/noL1GmpTJzWxjqfp9fnre4ZqJrSSal/m7WqaS60Xs9OWfMcyQYBO0Lvvo0tmIlrtLjCzTNK1+fEhyMaefINXrhHGXODZIZeKi+WrQ0XAx4hZtZxQ9DRnV1+kkFVoxjEU+YWWOQ9VTXFcaYalZo56WeOCFI9QXTvErb3sLlaJJEHYIDQvNcNGqVfKlCpFuEQUhWuQTtasUJsdYXVthZHyGqN0kZ7n4LQ8tTrAqZUI9oJVaRJrLmXqDf/K7/5xP/d7HmDNNgriJIW7Eolhoh2iuQ2zI5DXBkDW1K3pdyn210d8cOtVTr1aCt/iAyEwsjTGVhU9mCZGmXdK0iYxQielQq3fI0cC1NbT8BGFiE3srbMmFaH6VpbOn+d6BFZbWV/nAu36Wct4kbtYwHF1p3Oh2yJcM/Oaicl63NFkdiXEm8qSdNSoV4cdVLEcWowLSookVQTfqEMmCbupQpcvn7v0Mv/+//Bq5CAIHuoGOEWsUxAs/8TFimaCIWYJI25dS3hXFvJfZppQsKsvQmCYJzmKbPkZiELeTTJ+Q10i8OoFV5l/f96xS2Hzw9ikK5VHufeoML+w/yc7ZPG9647XMpzadQoHVeqgGqRELnEhsMyAIOqSObHcT4ect4iTFsmzCKMbQUWJbqVBQU2vRacepKPJ1zq6t0/ECtu2YoxiHuHXwK3nOeHXmkxxasUDL7/D8geNolsY1O3YojbcWh8R25g78cgxfNm+EwZR8aehFuSiDa/HYj3vi08gYvpWj4WtEuUlONRMeev44N9/0NqzCOKtrDV5Y9Yimr6KbG+Wj//eniYqzdIKEiZxOkS6GpaG5OULNxKxMYFqumrYboUNOK6F1UuFIGBRw9AppXEJPx7HDIlaUh8DCwuXQwaO4sh2DtIZrYmmwtTKKF/uK/5umw8mzaxw7dZZAtIa5bHFCuU1c4dneRbBdcLupdCHTRFN2VpFepeuEsgVOo8OR5SVCUvbs3M6Th55HMwyq3rJa3igVSxjxKW66ZivX7RrlWw98lUefP4leNNg16RCmOoeOrVAsTXH87DItv82+LRNcPT3L04fOsLq2zMzEODfeeBMvHD5KpBk8f3A/O3fuIGeb1NfXuOG66wmWO9y452biJqzh8v2nnuSGbbsV/33gwAG2TW3l1mt2kto50jTEtF21X4aoCGRNULS4mxmqXIDS/8ebHshD9Lua2FbIKkWIVXJpNkLue/B7nFqv04ojrltYx9KFtwW0Vo5T3j1PvdnF7q4wmSwwbTts3TrLydUGi0dW8eZLLNU7JGaJ+pkF7vvuw+zZM6/A/dA73spCpczpZpW//Pa3eO9ohb/85tcJU5O5XXv4rX//r7nn9XdTPbPIPXFEkZinH3qIv//hD/HJv/oGpqOxY+56zh5bpXTtrXziT/6Mv9dxCCJhP7KEFpPEHeVOobybxJnlFboyduFcD+c+N6C58rmR1L2BFmW0bgfSkNAe4/+69z7+0fvew2tv2cmTC0vcNred/PwcH3z9HSRrHQLLoePO4CWrlLtNOpOvxQ8XKY2N8mQ14OHjbV6zq4SnJdxww3X8z2/eTb5QIg5WuKYwyS0z08zOzuOfqtMpjPLufWP8xttvw0jLfPyn3sRrZ24irq1g2hGhewPLqwfYv9Lit9/2eq6ZbXP1bXOMnvJ4y0+8lqfWjmAkHaLAV5bKWl7snWUjFA9N37QTX1H4ezxZTF8u+mgycY5xdRvDtElaHSzDoOEF+MJD8yMYjo0XeOAFaoKAbSGLLL6REGmjdPJbOXXmBNsnc2yxTRqdhGbQIedajBdyuMoX0sS0HPxE5/Pf/Fu+9OCjHD27TGI7pLGBJt09STGLYmPngx4RJQGmYZF3TTpem2TUJXZnWLM0Pv3QV3j08AIPHzlFu5Aiu3HZuZwaMFPPR7dzytRWDB5fqSsDWaat5z6ym4oUQMJCUi1AzxWzaa0OY5NlTtebNP0U2i2wEjVqd4XabVO55SaWmAGM8djxBqdPPM9VswWuHauwuhYyUimSLxRI2uuUxaQ9NUnCgE6Q8oW/+S7v/Tu/ys6rrsWXjf0iiHUdw9cw2o3MpySVfeYsAi8gp3nohRHSaoTdatBJxvnMvU/wkbfexc/edD1xXCSMYzq+j+U4mS9goqtVb9nj6JW6en1mgxFXf9TtfSsTNM1SFOCaCW9/w2187vOfpW7C225/DaYdMyFNEnZxXR2jkxLWl/ny544offFv//33M1kJCMwJuvXH2Tk9giFyd3uNkuEoA8Vc6qldEUVI+KtvfoEjL7zAHa99A4UkQpxkbCfPVOoThQF6UCdvjqF1utidZaZm9rF3foIP/dv/wId+4Y28dscE/+TeP1cGCPOVlOLEGJHswKXk/YRU7DrE71tettHs/weIeCYnd/96wyvEKkdm2T2DvNQkbBwi1WvKymdJH2f52BGScpndYyU6jWMcOaJz1127CBsnSJISB9ttjGCEicpW9h//Km+8cQ+1+hT/7tsPcPueEd584/WsrCzRavvMTk2wuNpkcmKc022T4839zOUnmEk1TnZ1tk1H5JcjvtdpcdfOLZxp1jFTnYKWww3B2worq6K/DtiXs3GjgMc6XRy7wD7bpFlbRjMKzE+OYbTXMPM2USTyhYZ9xecil0rEMuPrgfzVDSD3XQ0ygV3NPL1F0NZI2jU6k6NoZ0PS8hi5pImRb2EEe0mLbVrrByhYW9SMqmtWCE6eYfyqIvW2zX/86yfwu6f4pbfcQaU8gmNoqsujW2qCIjuzGOYYa8lJxu0xaFShvJ22eYrCskVULmLGPl7cQjcK2LGL1qqxMmUw4Y0SN06huVuII7CKaxCYxMYECQ2MXBnN66J561ApEPlCzQbmsFX6C9B4KTeDQb7sECumR4GYBJjSbV3cWKeqQaO2xlQ+ISc0UVumFXdwc0a2pB8GeEbK6JRLUDvLij/N3n07mR+fZmpyTE3BxR09V3IR8zf5p4xG2mcZtUKCxknsXJFubRXKPth5tNBXVkniIqyZKVG3y2LHYzSRHREXWXJnsLQG44UGYcvFysvWEUsqf6XgUuJogua1WfUttZY7Ymo4YuRoyoDdI2sxaBQFkhj2aKaahKkt26R767K/3QbW+iLxV9BnZtTSgbJPZpgvmSXEaURiJsoIO0gd9p/s8ucPPsK3jh7hdDuiTYFIa+K7c4SGR6hsNAwmKRDT5Vg1z3i+wDt3OOwoF9VanpkX6i3QiX0Sw8S3TFq6RtdsQziN7tp07Rw4ZeyuRuAYtMQUzBJ7PJvUMDiTxPzOZx8kaohrsMVfPXuU7z67AFGKVpwg9dtEsriYK2BobYx8jq6YmOUcHjvr8aUnjlGPBThZVfeVN6wvtncyVTESZZMdiwuGbqjdHUMi2qLTfhnXpfR9USaWZuL44oVuUh0r8pt/9Emu3XIdPzl5FTOmTdvLEVoRk3WNpjaL5e5QWrlTocm6M8rH/vAz6IzhM04cjRNoJQr2JHXLoKuNU3dKNBkh1Ut0khEaRonQKFG1cgSpiaYXqCceYb4CnSQHU3IAABRTSURBVBSn5BC32jx4eD/eWouHTy0hXqLV2gq1Zp3QcGlaFcLSFB3dUpuniotwM7EI7LxYadCpLRKvtTFwCUpb0P0yWlDC14uYaZFW4BIbFdqRSWK56I5Laoo1lXS7l35tyi7U+JdE4vavVqht8lRF9JqYYtvUNGvrB7jv6BHuuW6Cs0+/wCNanflxlz/91n/mDbe/maS9zOcXjrH7i3/Gr971Dr584AmePfQkv/ju97N1dII/+ovPM5bEuCNbmCqk/M3+53nfTe/gDTds5YtPPMT3nzrCP3jjTXiOw+HmAj+7b0aZAuQSeGpxgV9457v5zrEnefu+cfIFR+2XETkVvvTofp77m68xf/MuXr93htGJOf7LZ76M167yiz//k7h2jgNnjvMHn/tv2Ftn+NjdP82Dh4/xpePP8ZbJGZbb6zx3/DTbZ7fxP7z1bsp+pIzOHLcoSxUvGeVNKVn4ZCAK+/Eyhq5TWF3nE7/+D/lnf/Av+c7KAYpTM/zN91/g0LGTfKu9TNg2eeTMad5191t4w64dvH7fdWzzXf7Xd7ydZ04dQ+T/D775PXzqzz/LaDPgwKkG77juBhaPr6KvefzyT72Pf/6ZP+PplUXWGh6//N4PMT+7i5NWxPLqIkluTBm4GG6Jp46d4Kpd23nw0EkivUJVBkpT59hqjf/zj/+EX/zgL3FitcXBNZ/PP3qY7be/mRvedA+f+Ox9xLZNbmqON93zFv7kmw/SCGIeO3qao806u6/Zw0/e9jZ+4W3vZ/V0jcPHF9BGK3g5ncVg/SUDLAk2BVkZWecK1Fp1MVFGq9W48+pr+I1/8EH+n7/4Ex5dWCLvuhQm9vKfnn+afdvGIVrnwOFDjJRM5vI5Fo2IctlkeXmZ7y+f4khtkadbp9GcgGrFZubmbbTGbOZv3cfeqRlWjJD50Qm8EyscXF7BjyPu3Hk9H3jLa4gbDYpWjhP1iPktVzM9XSbn5jhVbVAqjRJ6XZaW13nHPT+Lm4/YMjeHUZriu0+9wOmTx/HWV1ive8oox9Uc7ipV+MBdP8OxJ59l1ijwrqtuYTvQ1mMOrZ3l8NIiiWnSqbcxE4PZkekrD7LoqRI/Qesk2LpOPFdiPVzhzVfv4T233s23Hn2K9+65noeefo7mesJPXDfN+27ax/H1Np994DvUuwHRlkmWgiZG4qLnx9leHuf33/VBSDo49ZhibZ28p8PSIuNi9uYmuF7A33nT2/n0/ffyXPMsow0Y1bpY+RxWJ+aZI6dZObbCv/hXv03aanBosYEfG4iif3VpmYJjM2oluImH121TNFLmzBbbrSa//j++F71bwyrbmHGD+uIKYTHFGnNJmg1io8vv/8dPEBZMxuen6XQ7FHIFLB/i06s/AJDTFEdLqBSKJHHEeuix7CUcOHIGqwtTeYubts/xxMFD/MzNN9Hu1tRe9m+7+y5qzYCuM8r0Ypto1aM8OcY+s8LM+BQ3bp8mKhZxxbpH9lJPExJZFgpCosUq5tZZymNlbhyZpCFdvrrKwReOEukaoe5w7PQCv/y+n+d3f/ujvO/uO3jo4CFII1JLY/eunTz+vUdYqlY5c3YNw9SZGXHZMpJn17YtzE2Po5smZ9ZP81wnYWF9AX3bFlbDGraZcrJWZaYyzr7pbWp1Rcx5O0lMWHGJJgcby18O+U3ZhazOJHpCV/PoJjG5JM8zTz7Hw4dPEZspP3fbtaQzJY6fOcV77tpN3i/zzNFD7D/4DNfO78Nyyvza667hb599mh1XVyjrDe5/5BFOHX2Ghp/njm0TBJHF9XOTTJTGWK8kvGvvXmrNGo8cekqtbI9MzHFqdZ1nT7SVVWnXMMlbHrtHUmhVuWsyTy7vsqtoM+5a7J6e4ebr9vDg0wfpJC5WYvIzb3w9zx04zP1PHeTUmTMURiaZzcHTh9a5dX6MLaNb2V102FF0GStvoTg6zqHjR0QVk7nTpSZpJ8T2XvqgJw2gZnx0v3xhY2zQX6S6TeyfgGiZVDc5vlBXsqd4Kk2PT/B0vcMXv/gV/uHPv5OcEdDVErx6lZmxrdBNaHWa+FZMqSCThiIr1RYzhQBrYp7ltRpbnJhT1ZgJG5zxImvVKoV8iYUzC+QLo0xPT1Kv1kjDhKkRcTMOWG50mZzZTlQ9i5NzqS/7OOLNWsrjaglH9Uk6a6f5yiNPcNeerdx2w3XUV8/id9tYuQKF0TFarRrry2fZNr8D/BamZRO1Gsrhc7Gesnh2mW3btmH5DUZLeTTZhlgmIsP2oFMIXkqz56bVw0CWWWej4VHKVUm6pzDEcTE3BjmboNViqR3xh3/5V9y963re/frXEDohrcYq4zJbMg1arZjC7FbSxhKBeJymDuQrmLFHU+kXTHJaRKzn0A2dqNtQ3kzyXiOfV+NBHIVqppm6k3TXjlHMS2MZYiCtwNGMlMQu4LVb6DkX39D5p5/4zzjlAnEn5KMfeB8F28R2ZWExT9qqK3Us4rhpW5ieT2oaJKZF1GnjOjmSRMdrtciNj5J2u4ReB8O1M+NzUfMOvV4GyKlorvQSSXs/hlnN1J9eQpTEWKUyzS6c9WLmzBFyI7JifZCSnVfbpTc6LWKzRLPZZiJnka8UCboenmazuFbjqu1zaP46Qa2p1ue6nYByzkEWOoVPC9EEUYhVKFI9e5ajNbhmbpSSrFb7ooK1lPG3ho9XyON5PkGcYBdGaVTXWfcttpaLTIpGMw7o1NbUwqwjVqQyhRaKlBVsXSdSQNtqdidyppl0MEfLtJaXKIyM4nndbPt3XcNJNpv1DQb50tCNrSSbh7TrhGFI4gdETdEjjOCRU9uj20nA9vwIIhMFnRq24aLLZv4Nj9Ss8NiZVf7wzz6H5o7j1VvKTUF00R/52Mc5dOggUbtLmBvF0jRyY9NKQe/Hsu2NRSAqbTMHmsXBU4t89aEncCoTRHGKUSqTOC6+bhC7RegYFPUR7v/Stzm7/wxzTo7rytsYSTQ6zZZyjctvmcUZHVE66VTANRySWCc1HPxIUwsTuoTblrLNkK157Jz4xyQ4hTKxmIOJA/7LuDYFWc34DF2tkemyRGTlqYU2R1c6nK63kd4fVmvU9IQn104TRhpJmOKbJiuNDovtFpWZGbqdGrligTDscGjhLJPX3c4TB0+g5Yp09BzVVpsDi2usdyLSXIWOZnNspcaaF9MSpX5hhLUQzjY96t0IP0w5ubRCkpc1wzZHV2osd31G916Fs3073dYSR5pVVlZOYRXKilplndL3Q+UqJwcfJLL/vviltNvkSzmS2EMnUL4xsk4et2T1xSUJNNJuiBGJVuzlDXybgiy9KtRTorBDmvp0kw7PHn2WA2tr/LevP8TxRsLnnzvGn977VQ4cW+VffvkxmqbG1w7U+dzjh/nmA4/RjG1GR0ahekLpEe5/4jk+8s7X818PnVGs4YlDp/jj+5/nu48f5h//16/RsHVW19d4/PBhPn7fYxxeiWkFCXHJ5eCJU3zh+YOsNdv80SPP0GmkfPwrD3Ds5DHaic43jy5yWkv4xkLKNx9/gGcbNeW/rVzewhRRp7r5gjp5R232Ess+HDIbSJXmzUxiDPGPQbyr5OgPQ3njyl50spvBZo6SmxH4piBLwo5l4BspqdcmZ2js3bWXvTO7calw6MQyTzfalApjvOmmu/nasSXWq+s8vf8EO+Z2cOfVV5N0I+rNNolt4SUORmmG+RGbh5e7JIFPdb3GmdTirttu4YHvL9KpNRjF5nW33sGRhS4LxxcYTw38KCHttjlW67JQ6+IXRujILHKxxe3X38xoV+fJQ8cYDU3u/9IzzI6OcuNVtytfF1FVige/7KCIHLGRROhmb7szU06diDFkp3HlYmwqUTETsGRFW45kEuOIRA3mm4E57NnmIKdQXg8pdmx0e4zYKvGd51/g333jPh5dPEkadrGtiO2zE0yWXXIjOkG1xmwu4LYxjdtmyuS9FvlcmTg3zeEzHmdXG3z7mQMUkwJHY/HRyzPhJuwc8VkPqngTIxwMu3zyrz/H8cYpmrkuzVJCTh9hfm6WKc3moefOcIuZsHVLjlG3xKceeBB7chJrvkzYOsGbf+7N/Ie//TKPH5dJSorZO3tKzjSRS1leXHGF/TCIL6O7UOtQY3lCIybxPNpeyKf/9LP8Tx/4ZV5z4y14YosWizuvhqU5tOMWYWDjlMuY+XFWxSgwX6QbxMQtn1PrLa6bH2H7VJl333At9+1/gUB3ZQsAzILF7NhW1s40eeLRI9x1wxu446ob1dkjej3B6wZqkWBubJzvHDjFT+7ZijGi87995FfxumXu/c79FE62iIMur73+Vn7rnl/h6/c/QrVWJY5jdd6I7D6jmabSKMaimH+FrstQckoYdklcC18WH4t5zrY8TlZPsdJYItRyylhQNhlJUhezVacwtZVTDY8vPv0cjy2s0HKKpMUCZtHhhcPPsqvi8/ar5nnn3klOHz1JIU3Q0xx+qNFtrpMbGWUt0OnGBqsra5iOQ2yLnreFUSgp48J6GJJaIbWzSywvvEBhehrLLmKUHBzHZXFhjdUgYG5uR7anRW+LNYWpOMSb5gX77P+gsd5Un6y8nsLszL04EBuMlPfecwcHn3yAccNg+3gBzZxC/NC73SXuuWkfhpVw/Y4tHD1zkpIFo1tklaJBGNTYNlFk57Zp7FDnzt3j7D9SYMekS8A0ehzx07ftJBdUueaqnTz73EPs2TbFWF5HC3Xu2DVKzh7DMjXeeP11lMYmaZ5t8PzDXyIsbOOm227j2WSOcSfPV77+NZbcKldPzVMuldVmT2LLJ3vBGIr/ytKU8OQfNLxZ/ptOq8WiXezfkuZhEq2hupzYAIvRiaElhGIvkAaUNJklRTScLnlK6GLvknbRLBGKRqiETSytxYo9gW9GzNZGSQo1fGpo2hgNz6RiL4FWQfdX0Nx9eP4SdavCWFwjH9t4dkCtmuOz93+ZHTM3c/udM0z503S0ZzGtCrkw4VjOYmvsQXOajlPFdIvYIpqJBakwNV1clsVNWPYBFRPgzTvyS2+CS/O7rH2y+O5Zyp7XUEaF8lJHTAVMMdgLkR0spKC6LEYmEaPKbzpUI7EtspESjuTIoIRUd6nEgVpF1MwqRhKTx1XbNkyIFTxi2ROhOWXSZB3T1LDihjoKTk611CyTlepRtpVtXnfDODmxL7bqWL6LayonQ2blHCpZ/HTqlE2xe5YlJqWhUSVVoClwxahmk52eXjq6m6a4DLtQOMnhTGqUVpveJdLpRObsHd/T22RD9qA4588uhsdyKctJcR0QwOXAOfF837iBQLb9f7bhhZi/SyLxqBYTMY2cJOt1adlUam5+mpFKntGKo2aLFBOcWPYtypyo1QGTEl9ZJm0Y1fsKL6mO2lLnihtcZPUd8v/yIA9J+IoHewFjI+OMFkfERkHpL7RSv2Fe8dK8pBf+yIAs+o2w0VCb+ouvSK6QA99TJ6EpncNLqvYrG/lSTv3Kvv9Fv00OOpTdYiw5MVj2yBf1ZOih5wbvHvOiM34FIv7IgJwmEaZloJuGkhJ8r6V23UKmxz/k148MyJEvGrCUSCQUXQyFEoxinkDso3/Irx8ZnixuxiJp6LIqEomeX2ZAsn+oWJL/cKP8IwNyf4OlvjSm7n9Edg7/kWEXP9y0unnpXgV5c3yuyNNXQb4iMG6eyasgb47PFXn6KshXBMbNM3kV5M3xuSJPXwX5isC4eSavgrw5Plfk6asgXxEYN8/kVZA3x+eKPH0V5CsC4+aZvAry5vhckaevgnxFYNw8k1dB3hyfK/L0VZCvCIybZ/IqyJvjc0WevgryFYFx80xeBXlzfK7I0x9rkMWwSJyLxBRZfss/2T5S7JPlWx1LL+tZmqZOD1ZRsmhqcym1e42k6YVtjvjwhcYfa5AVeLLjp6AkTjyxuLNpBJFs6Cpgy+ElGqmuESvwdVJldiYnXSZgWMSxgKz3zu4TuDKLULEKPfc593xwM/zILKQOLv7lQlOSSM5w7R0wbonNhpzTmtna6YZB7PvKw8nK5Uhkp1tl16F2z5GlcWkbMURQ9vDKLU22o+yt5vaPKEp7u9dqQxwpf6wpWcxkDddCTjkTH0I5OLHb7ihXtjCIlYGkGDYaYpEktKqnEMsGmZHsoaL8FsUZUxpFGUVqsqNL9hGAlfGiGJXLSZvmcHr9sQZZuGTUailzXXt0jCjWsMuTBKGBVZogiTR0p4CeK2X7NTuu2h5HTjaWS9zS5FJsQQyC5eyUHsjyLW4S6hNF5+KqBBf9Gw7/RRF/FG81R3Y2FAdyg6Qpp1jqfOEv/oJieYzrr9nN9rkZbN3Fa9aQQx3LshuC7ISrC1sxiHwfscHTTTEYF9fqGFP2OVOjqGxuIHbaMogK0x9+/ViDjIAkJ7F54h6Wo+V32TK3l1279+F3ZY8Mk061xQsHDjI3NwNWSx1VGovjQxTSbDYpl8sY4j0FBJ6HK2dg9a7+cdPKbrsfOOD7xxpkoTDZpEl6f+DHPPzAI1RGp6k1Guq0S9kJMw5TFs428eI8lVpKMW+ycrbK3LZtHD68xOh4qE6wbDSahGGCbUAh5xLHHsWCw8z0GLYjm0CF4lo5AGIxa/8xvpSEG3QRyaHb8tg2v4sjx04zsXWMdrdDq9ugoNuUihMcOtZgpKypDUieeOo4E9PX8sLhFUarAWMTkxw9egbXKavtGGamDQKvzsSYw8TUOI4pbsTCv/9/CLIuZ/clMWkUUCwV2L27QscL8bpd0ijG1lJcI+b6q7dRmegQ+B5X75xmbNRgbkeet731JtxcDk136DRq6oD0W27eRaVcQEvHsayEvJvtjG+qPfMHU+yPNSUrIRfx9PUyv2rXVcdCR5GPpRsUHZuCmVIaH8Us2CwtLVIZNxjbModhtNmzeyxDTcuzvn0Sr6uzb+8oWiI83lJbxMuBkHGYkMShOqhxEMzagw8+uPnQOCjVq2EvCYH/F0EE3RHYL3QwAAAAAElFTkSuQmCC) 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Integrability of Dynamical Systems: Algebra and Analysis |
X. Zhang |
Springer |
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) 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Frontiers in Applied Dynamical Systems: Reviews and Tutorials |
M. Beck, H. Dijkstra, et al |
Springer |
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) |
Mathematics of Epidemics on Networks |
I.Z. Kiss, J.C. Miller, and P.L. Simon |
Springer |
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|
Ergodic Theory of Expanding Thurston Maps |
Z. Li |
Springer |
![](/Portals/DSWeb/EasyGalleryImages/2/1321/Goodson_cover.jpg) |
Chaotic Dynamics |
G. R. Goodson |
Cambridge Univ. Press |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Ammari-cover.jpg) |
Evolution Equations: Long Time Behavior and Control |
K. Ammari and T. Gerbi |
Cambridge Univ. Press |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Dorodnitsyn-cover.jpg) |
Applications of Lie Groups to Difference Equations |
V. Dorodnitsyn |
CRC Press |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Akhmet-cover.jpg) |
Bifurcation in Autonomous and Nonautonomous Differential Equations with Discontinuities |
M. Akhmet and A. Kashkynbayev |
Springer |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Katok-Cover.jpg) |
Modern Theory of Dynamical Systems: A Tribute to Dmitry Victorovich Anosov |
A. Katok, Y. Pesin, and F. R. Hertz (eds) |
AMS |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Isaev-Cover.jpg) |
Forest Insect Population Dynamics, Outbreaks, And Global Warming Effects |
A. S. Isaev, V. G. Soukhovolsky, O. V. Tarasova, E. N. Palnikova, and A. V. Kovalev |
Wiley |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Harne-cover.jpg) |
Harnessing Bistable Structural Dynamics: For Vibration Control, Energy Harvesting and Sensing |
R. L. Harne and K.-W. Wang |
Wiley |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Asch-cover.jpg) |
Data Assimilation: Methods, Algorithms, and Applications |
M. Asch, M. Bocquet, and M. Nodet |
SIAM |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Turner-Cover.jpg) |
43 Visions for Complexity |
S. Turner |
World Scientific |
![](/Portals/DSWeb/Users/073/89/2889/Book%20review%20covers/Differential%20Dynamical%20Systems,%20Revised%20Edition.jpg)
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Differential Dynamical Systems, Revised Edition |
J. D. Meiss |
SIAM |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Grines-cover.jpg) |
Dynamical Systems on 2- and 3-Manifolds |
V. Z. Grines, T. V. Medvedev, and O. V. Pochinka |
Springer |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Goodson-cover.jpg) |
Chaotic Dynamics: Fractals, Tilings, and Substitutions |
G. R. Goodson |
Cambridge Univ. Press |
![](/Portals/DSWeb/Users/073/89/2889/Book%20review%20covers/A%20Course%20in%20Differential%20Equations%20with%20Boundary%20Value%20Problems,%20Second%20Edition.jpg) |
A Course in Differential Equations with Boundary Value Problems, Second Edition |
S. A. Wirkus, R. J. Swift, and R. Szypowski |
Chapman and Hall |
![](/Portals/DSWeb/EasyGalleryImages/2/411/BarriersAndTransportInUnsteadyFlows.jpg) |
Barriers And Transport In Unsteady Flows: A Melnikov Approach |
S. Balasuriya |
SIAM |
![](/Portals/DSWeb/EasyGalleryImages/2/411/Kutz_Cover.jpg)
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Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems |
J. N. Kutz, S. L. Brunton, B. W. Brunton, and J. L. Proctor |
SIAM |
![](/Portals/DSWeb/Users/073/89/2889/Book%20review%20covers/A%20Guide%20to%20Temporal%20Networks.jpg)
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A Guide to Temporal Networks |
N. Masuda and R. Lambiotte |
World Scientific |
![](/Portals/DSWeb/Users/073/89/2889/Book%20review%20covers/Lectures%20in%20Nonlinear%20Mechanics%20and%20Chaos%20Theory.jpg)
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Lectures in Nonlinear Mechanics and Chaos Theory |
A. W. Stetz |
World Scientific |
![](/Portals/DSWeb/EasyGalleryImages/2/411/Steeb_Cover.jpg)
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Problems and Solutions: Nonlinear Dynamics, Chaos and Fractals |
W.-H. Steeb |
World Scientific |
![](/Portals/DSWeb/EasyGalleryImages/2/411/Haro_Cover.jpg)
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The Parameterization Method for Invariant Manifolds |
A. Haro, M. Canadell, J.-L. Figueras, A. Luque, and J.M. Mondelo |
Springer |
![](/Portals/DSWeb/EasyGalleryImages/2/411/LanWen-Cover.jpg)
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Differentiable Dynamical Systems: An Introduction to Structural Stability and Hyperbolicity |
Lan Wen |
AMS |
![](/Portals/DSWeb/EasyGalleryImages/2/411/Skiadas_Cover.jpg)
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Handbook of Applications of Chaos Theory |
C. H. Skiadas and C. Skiadas |
CRC Press |
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/BadziahinCover.jpg)
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Dynamics and Analytic Number Theory
|
D. Badziahin, A. Gorodnik, and N. Peyerimhoff (eds)
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Cambridge |
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/LucariniCover.jpg) |
Extremes and Recurrence in Dynamical Systems |
V. Lucarini, D. Faranda, A. C. M. Freitas, J. M. Freitas, T. Kuna, M. Holland, M. Nicol, M. Todd, and S. Vaienti |
Wiley |
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/SkokosCover.jpg) |
Chaos Detection and Predictability
|
C. Skokos, G. Gottwald, and J. Laskari (eds) |
Springer |
![](/Portals/DSWeb/EasyGalleryImages/2/1198/Brauer-cover.jpg) |
Dynamical Systems for Biological Modeling: An Introduction |
Fred Brauer and Christopher Kribs |
CRC Press |
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/HietarintaCover.jpg) |
Discrete Systems and Integrability
|
J. Hietarinta, N. Joshi, and F. W. Nijhoff
|
Cambridge
|
![](/Portals/DSWeb/EasyGalleryImages/2/411/CoverNotAvailable.jpg) |
Continuous and Discontinuous Piecewise-Smooth One-Dimensional Maps:Invariant Sets and Bifurcation Structures
|
V. Avrutin, L. Gardini, M. Schanz, I. Sushko, and F. Tramontana
|
World Scientific
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/PikovskyCover.jpg) |
Lyapunov Exponents: A Tool to Explore Complex Dynamics
|
A. Pikovsky and A. Politi
|
Cambridge Univ. Press
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/AravindaCover.jpg) |
Geometry, Topology, and Dynamics in Negative Curvature
|
C. S. Aravinda, F. T. Farrell, and J.-F. Lafont (eds.)
|
Cambridge Univ. Press
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/LiebscherCover.jpg) |
Bifurcation without Parameters
|
S. Liebscher
|
Springer
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/JacksonBiologyMedicineCover.jpg) |
Applications of Dynamical Systems in Biology and Medicine
|
T. Jackson and A. Radunskaya (editors)
|
Springer
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/CoornaertDimensionCover.jpg) |
Topological Dimension and Dynamical Systems (Universitext)
|
M. Coornaert
|
Springer
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/ChenComplexNetworksCover.jpg) |
Fundamentals of Complex Networks: Models, Structures and Dynamics
|
G. Chen, X. Wang, and X. Li
|
Wiley
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/ArgyrisExplorationCover.jpg) |
An Exploration of Dynamical Systems and Chaos: 2nd Edition
|
J. Argyris, G. Faust, M. Haase, and R. Friedrich
|
Springer
|
![](/Portals/DSWeb/Users/079/95/2895/MyBookCovers/LugiatoCover.jpg) |
Nonlinear Optical Systems
|
L. Lugiato, F. Prati, and M. Brambilla
|
Cambridge Univ. Press
|
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Dynamic Systems: Modeling, Simulation, and Control, 1st Edition
|
C. A. Kluever
|
Wiley |