ung dung dao ham giai pt, bpt, he pt

... hàm số f(t) đơn điệu thì (1) suy ra x = y. Khi đó bài toán đưa về giải và biện luậnphương trình theo x+) Nếu hàm số f(t) có một cực trị t = a thì nó thay đổi chiều biến thiên một lần khi qua a. ... phương trình, tôi đã tổng kết lại một số dạng toán và phương pháp giải như sau. II) Một số lưu ý chung: Để học sinh có kiến thức vững để giải các bài tốn dạng này u cầu học sinh nắm vững một số ... > 0y > 1 thì f’(y) < 0 suy ra f(y) < 0 vậy y = 1 là nghiệm duy nhất Nếu x ≠ 1 theo trên y, z ≠ 1 hệ đã cho ⇔ln1ln( 1)ln( 1)y yxyz zyzx xzx=−=−=−...

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... . . . . . . 31.4 Phương pháp nghiên cứu . . . . . . . . . . . . . . . . . . . . . . . 42 NỘI DUNG 52.1 Cơ sở lí thuyết . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2 Ứng dụng ... tập điển hình của từng dạng, động viên khuyến khích học sinhtìm lời giải hay hơn.• Sau mỗi nội dung dạy trên lớp, cần chuẩn bị các đề tài phát cho học sinh vềnhà tự học kết hợp với việc kiểm ... biến thiên của f(t):tf(t)f(t)−∞−2252+∞− −0++∞+∞22227474+∞+∞44Chương 2NỘI DUNG Trong các kì thi đại học và cao đẳng, thi học sinh giỏi cấp tỉnh, thi học sinh giỏiquốc gia...

... b)(1)dxys y xs x e ++= + + += +Trừ vế theo vế của 2 phơng trình trên ta đợc : a b a bs s c(a b) d ex yy x x + + = + + + Mà theo giả thiết ta có : d ac ,e bc = + = +a b ... =.Ví dụ 2 : Giải phơng trình117 6 5 (1)7 6 5 (2)yxxy−−= −⇒= −. Trõ vÕ theo vÕ (1) vµ (2) ta cã :1 1 1 17 7 6 6 7 6 7 6 (3)y x x yx y x y− − − −⇒ − = − ⇔ + = +XÐt ... nghiệm của (2)Xét hàm số ( ) ( 1) , 0f t t t t = + >. Khi đó (2) (2007) (2005)f f =Theo định lý Lagrang c (2005;2007) sao cho '(c) 0f =1 1[(c 1) c ] 0 0, 1 + =...

... ra (3) có 2 nghiệm phân biệt .Các bạn có thể tham khảo thêm tại: http://toanthpt.net/forums/showthread.php?t=13598Nguyễn Tất Thu - Trường THPT Lê Hồng Phong - Biên Hòa - Đồng Nai www.violet.vn/toan_cap3 ... hàm trong các bài toán tham sốCHỨA THAM SỐ Khi giải các bài toán về phương trình, bất phương trình, hệ phương trình ta thường hay gặp các bài toán liên quan đến tham số. Có lẽ đây là dạng ... (như xác định tham số để phương trình có nghiệm, có k nghiệm, nghiệm đúng với mọi x thuộc tập D nào đó… ) và phương pháp giải các dạng toán đó. Bài toán 1: Tìm điều kiện của tham số để phương...

... tiếp tuyến đó vuông góc với đờng tiệm cận xiên của đồ thị hàm số. Chứng tỏ rằng tiếp điểm là trung điểm của đoạn tiếp tuyến bị chắn bởi hai đờng tiệm cận của đồ thị hàm số.GiảiViết lại hàm ... điểm A thoả mÃn tính chất K để từ đó kẻ đợc k tiếp tuyến tới đồ thị (C) ", ta thực hiện theo các bớc sau : Bớc 1: Tìm điểm A thoả mÃn tính chất K, giả sử A(x0, y0).Bớc 2: Phơng trình ... có cùng hệ hệ số góc k. Gọi các tiếp điểm là A, B. b. Viết phơng trình đờng thẳng chứa A, B theo k.c. Chứng minh rằng đờng thẳng (AB) luôn đi qua một điểm cố định.Giảia. Xét hàm số (C),...

... nguyên tắc theo chiềuthuận, tức là từ bất đẳng thức giữa a và b, dùng tính đơn điệu của hàm số f đểchứng minh bất đẳng thức giữa f(a) và f(b). Bây giờ chúng ta đà sử dụngnguyên tắc theo chiều ... 3.Vậy, với m > 3 bất phơng trình có nghiệm.Chú ý : Tiếp theo, chúng ta trình bày các ví dụ với yêu cầu " Tìm điều kiệncủa tham số để bất phơng trình nghiệm đúng với mọi x ".Ví dụ ... thêmrằng bớc tìm các giới hạn trong bài toán khảo sát hàm số là cần thiết. Ví dụ 3: Biện luận theo m số nghiệm của phơng trình : x + 3 = m1x2+. (*)Giải Phơng trình đợc viết lại dới dạng...

... chọn đề tài nghiên cứu Sử dụng phơng pháp cục trị để xét phơngtrình, bất phơng trình.II. Nội dung nghiên cứuA. Lý thuyết1. Phơng trình f(x) = m có nghiệm trên D )(max)(min xfmxfDD2....

... đạo hàm để giải PT, BPT, HPT chứa dụng đạo hàm để giải PT, BPT, HPT chứa dụng đạo hàm để giải PT, BPT, HPT chứa dụng đạo hàm để giải PT, BPT, HPT chứa tham số tham số tham số tham số trần mạnh ... ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa dông ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa dông ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa dông ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa tham sè tham sè tham sè tham sè trÇn m¹nh ... ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa dông ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa dông ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa dông ®¹o hµm ®Ó gi¶i PT, BPT, HPT chøa tham sè tham sè tham sè tham sè trÇn m¹nh...

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1PT0 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1PT0 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1PT0 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RFiYiIiIuLk11cmqalpqbquu52u91ud3x8fHh4uG3bOTk5kmrp6elSckVFRUVFRamqmpmZKZ/JzMyUAUPl5ACm/AxOXDk/nhNRzsih/K0zT9ZsHTwLQECkAZ1Xbm5uly5dunbt6tRPuq6npaU5I4EJCQmxsbFycUREREJCgjTq1XU9MzNT8iMqKiomJiYsLEzTtPT0dJn6ap2TVS3rqmYNFZvVXs32dbX8QoBIAzqpZ555RoJK0zS3221ZltvtTktLc2qgmJiY+Pj44ChyhvikYJJVIc7nmy304AmDSANwkcycOVNRFMuynHa9TjgpJ1dttOxNFbxmJHixhqySJ9JApAG4BJzlFUrQwnfl5BGXrbfIc9ZryEoN5aejiB0mzwzDcI6JCW72yP88RBqA9uuU3YFP14RQ+WlLX2dHmvLTzrxt/HZt/8Eu5g3lSqlfnfUpMtB67t+atsXt54ZEGtBB0M229Ss1TWtqapIFL87IqtRttC3uMG2L2fkBoFOQOcKCggJpqazr+ocffqjrOgOPHeoXu7bXfQA6QJXWaQU31nJaRLrd7qamprN+4G63W7YAnnG2MtQ16+3SrDYKvkb5aY/QZiPYwXeQDSTBw7/BWyed1m7OLK+zt1LI+ebOYHJTU5Oqqgw8Ah2EvLfidOSd8dNPP50yZYq8RQ4bNmzt2rWyOe/sbmia5osvvnjzzTcPGjSow/9KEbwd3mm6ppzcNe+0gAlOLKc3TXCzGCfbnIPLg69xPtA07dixY3v37g0LCwsEAnV1dd9//31wpJWUlOzbt08SURrcuJzFPwA6SZXWaefSpAi47rrrPB6PvPm+9dZbEktnsV1BbiglQsvWJyH3cFq/0qm6gk92dT5vmmazttfN/tPZKFJZWbl3716/368oyuHDhw8dOqTrellZ2YEDB2SaU1XVQ4cOHTlyxPlymfWUpT3NfmmTv5U2pIqiyF5MIg3oXJF2Ia5s/zd03mfj4uICgYC8RXbr1k3eLoNv8rNu6KwRbaUjZUg8nNavlNi2bbuwsNA0zcrKypqamrq6Op/PZ1mWz+c7ceKEZVlyBHlNTY3X621qavL5fFVVVYZh1NTU1NTUBGdn8DCmvC7NmovKd4yKikpKSpLxScuysrKygp9zZGRkQkKCjP26XK76+vrw8HAiDUCnEDzwJdNp59js35kHCh5ta1eatYBxcr1li+pml8mRrRUVFT6fr7a2VjLM5/MVFBRYluX1equrq+vq6rxer2VZtbW1FRUVwfcMvlXwE3a73RkZGfL8Y2JiEhMTFUUJDw+XZJJmoRkZGfITmqYp1zg51yzSunTpkpSU5LysYWFhzKUBQKeo3Z2wCe6CJoOuXq9XjmktKCgwDOPIkSM+n6+ystLn89XV1TU0NJSWllZXV/t8vuA1GsELPaSKyszM1HVdWomappmWlhYREWFZlnxGgkr6XCuKEhsbGxcXp6pqZGRkfHy8bK6QrqQSb87Gf6eHQCAQCJ4sc34vcc62JdIAoCPnmTOJGLz3rrKy8vDhw+Xl5dXV1aWlpYWFhcXFxZWVlUeOHDEM4/Dhwx6Px+/3O53VnBmy3NxcRVEkhJKSkuLi4hRFiY+Pj46Otm1bTmyQALMsKzk5OSoqyjTNhISEhIQEGUt0TmBoWdQ6p7E7eRZ8il7wlKfzDwm+QGKVSAOAjkmqHF3X6+rqjhw5UlRUVFxcXFJSUlpaKh9UVlZKBaYEHWgXFhbmcrmSkpISExPlBKK0tLTExMTY2NicnBxFUaKjo2NjYxMTE6ULdnR0dHx8vLOC0ckqSaZmqx+bLTMJrvacskxir9nFLUd3nbh1llwqdA8B0DEYhhH81ubUBMElSwdYZy9v685eLmdRu3RCcf6NlmXV1NT89a9//eabb9atW+cc/Rq8QEM+Y5pmbm5u3759c3Nzr7766pycnNzc3Ozs7GYlkdKGhZHOPZ2ICn74p6sjlZ+Ojp7y+lOuKT3l/Yk0oOP8Sn6prmwPN6ytrd20aVNBQcEXX3zR1NQUGRmZnJw8Y8aMAQMGyKr94OudIiB4OcNZf+uL2ePRGZcLfme3bbu+vv7w4cNSe33xxRc7duzYs2ePYRjyb/R4PLGxsSkpKUlJSfHx8ZmZmZdddll2dnbXrl3T09MzMzNPecR5KP6fQ6QBHUQn35e2Y8eOefPmpaWlvfnmm6Zpbtiw4aabbqqqqpo9e/Zll13mbPUNLgucP0Oux6MUarZt19TUHDx4MD8//9ChQxs3bty7d29RUZGzW27AgAG5ubmpqalpaWlZWVm5ubm5ublpaWlyannwSKAzxCfZL0cUheL/OUQagI6gtLT0yJEj0uPK4/GMGTPmD3/4w/PPP5+Tk/P73//+XBbrtxNO8SSbi4uLix988MHNmzfX1tYqimKaptvtDgQCuq7PmDFj1KhR48ePT09PDz7iVWlxpI6zbMSpWUN9bJZIA9ARjB8/vkePHtLdSmbRNm3a1KdPn27duilBK9dD9F8n6w9lIPHjjz9+5ZVXNm/eLEWVrKeIjIycOnXqpEmTbrnlFlk6H9yG6nRzVM3Wbig/naAi0gDg0oiOjh4wYICEmWEYhw4dWrVq1d133z106NBQjzQJLdM0a2tr58yZ8+qrrzrNfD0ez6BBg+64446pU6dmZWUFdxYOLs46DyINQEcgw3FO13nTpqsAABe5SURBVMG3335b1/WHH344JyfHCYDQ/dfV19cvWLDgpZdeqq6ulp1Ybrf7t7/97R133NGnTx8Zb2zWWUr56eHmRBoAhM57mcslu3GPHDkye/bsnJycXbt2JSQkVFdXx8bGhsoskaxmNE1Tyqzjx49v37598eLF69at2717t9vtzsvLe+SRRwYPHtyvX7/ExETp5OvxeILb2CuhP35IpAHo1OTN3efzrVq1Ki8v77e//W1CQsK3337r8XiuvPLK061Kb1cklhoaGtxut67ru3fvXrJkyeLFi/fs2VNXVxcfHz927NhbbrnlzjvvdHYxO+sSW86Edc6zMIk0AB2BYRimaa5YsaKqquruu+8uKSk5fvz4/v37s7OzlZ+zXvwSUlXV7/e73W5N03bt2vXCCy+sW7euvLxc1/XevXs/+uijI0aM6N+/v9/vDw8PDz45DEQagA4lEAh8+umnL7/8cm5u7s6dO2UILj09feDAgaGyMN1ZYf/555+/8cYby5cvr6+vz8zMvO6662688caZM2c6/Xlb39xNpAFAaJs3b97zzz/v8Xjy8/OdsyLvvvvu6OhoJWgrcftMMmdctLGxcfr06Z999pmiKJGRkbNmzXr88cfz8vKco59VVZWm9Z12toxIA9Dx/e53v5szZ47T9FYO+WxoaJClE0r7Hns0TdM0zYaGhvnz569du1bW38+fP3/69OmRkZHBm8bk38XLTaQB6NDvZS6XcyiJZIDf7/d4PM4K/nabZ/IDV1dXz50797//+7+lG/0LL7xw1113yfbqsLAwXl8iDehcOnnb4uBGGEpQ+yink2Fwa6h21bbYtu3a2tonn3zy7bfftixr9OjRzz777ODBg+UL3W6303efF5pIAzqLTt62uNlwXLOpJufKdtK2WJoOy04ywzD69etXXl7u8XjuueeeV155RXqFnHKA8bw/7ZB7oVu/jEgDgEvz+4dt242NjYsWLSopKVFV9a677po9e7Z02ecRnR3WzADAxeaswPzyyy/feOMNVVWHDRs2a9as7OxsyTMWNJ4dqjQAuOjFhKYZhvHhhx/Onz//+++/79mz55///OdevXoFAgFpiNUJ2zMSaQAQkizL2rx58yeffJKfnx8eHv7000/36NHD2XNGnp397wo8AgC4yEzT/Pzzz9evX2/b9hVXXDFt2jRZu8+TIdIAIPQibfHixWVlZampqbfffruqqrquh/qJ0kQaAHRGL7300o4dO6Kjox955JFZs2Y5za54MkQaAIRGZWYYhmEYpaWlc+fOtW17/PjxU6dOdbvdLpdLqjTZryZ/BgIBwzD8fn/nXNNvWZY8sRUrVrhcLpfL5Xa7d+/ebVnWjBkz5LyCX/3qV7Zt+/1+Ig0ALioZXVQU5d///d8DgUBGRsaNN97Yo0cP5wJnZb9k2x//+McHHnigoKCg064WkYaWY8aM2bNnj6Io999/f1ZWlmEYo0aNeuWVV7xe77x58wzD8Hg8RBoAXOw36EAgUF5evnDhQrfbPWbMmMGDBze7QHouy5HW+/fv37p166ZNmwzD6JxPTPqnhIWFyZmub7755l//+tfq6uq9e/fecccdXbp00XXd7XYHAoH/+xL+PwOAi+a+++6T8wGmTZs2aNCg4Ldjp+GkaZrl5eXr1q07fvz48uXLBw0adPnll3eqpyQzi8GNOp988sm+ffvec889//AP/3Dw4MGYmBi5QPnpngeqNKDjFAFtcd6vbP83dK483Z/ncsPWv6TZ3x44cGDDhg2KoiQnJ48YMSL4KBy5lWEYgUBAVdWlS5eOGzcuMzNz7dq1q1evrq+vl7mlTvJCB6+UkSvDwsKioqKmTJmi6/rf/va3+vp6p+u0YRjODanSgA6CbrZtufISti1WVXXNmjWNjY2qqj7xxBPR0dFShTj9HuVwHFVVS0tL//Ef/3Hnzp1hYWH/+7//u2XLlptuuql79+5ut7vztC2WCsy5YMWKFYcPH160aNF33303YsSIwsLCp556KiwszOVyyS8BckOqNAC4GDZv3rx69WrTNIcOHfrQQw9pJzkXyACabdu//vWvv/rqq5ycnJEjR3br1m3NmjWLFy+Weq5TPTHLsmzb3rdv39NPP/3UU09NnTrVsqyrrrqqd+/e77777gMPPPDWW29JCzHnS6jSAOACktPObNv+4YcfduzYoSjKXXfdFR4eLvkU/HZsGIau68eOHSsrK+vfv7/b7R45cuT69evfeeed7du3y6hjhz/S2jAMOc1VFojKBxEREbIeRJ7kL37xC+foO13XiTQAuBicsbWKior8/PzS0tLExMRJkyadstG+qqpNTU3Lli2zLGvevHlSo+zdu9fv92/btk3WPXbgJiMyWajrut/vd7vd8s/Udb13795z5sxx/tWapv3xj3883U0YeASAC8WZ48nPz9+9e7dhGNddd11WVtbp3tMNw/j222/HjBkj82oul+vqq6++8sorDx48uGPHjo5dojmF1+kmJtuCKg0ALqxAILB79+49e/ZYlnXnnXfKQseWl+m67vV6s7Kynn76admaZpqmz+dzuVzbtm175ZVX3nzzzQ6canLMt4y+SqKfTS7yfxuAzuncV1vIuGKzhlVOT30ZOTQMo6Cg4LvvvistLU 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